Like a sleeper cell awaiting activation, a never-before-seen Windows backdoor dubbed Sleepwalker waits silently in memory for one specifically crafted network packet to wake it up and deliver commands using the malware's 23-instruction language. The commands can do everything from running code directly in memory to moving data off the computer. Malware researcher Dominik Reichel discovered the passive backdoor, which also has its own command language, and detailed Sleepwalker in a technical analysis on Monday. “What makes it worth writing up is what that packet carries: not a readable command, but a short program written in a command language of the backdoor’s own design,” Reichel said. “Its 23 instructions cover scheduling, several ways to move data, staged file delivery and running code directly in memory. Recovering the encryption key is not enough to understand one of these programs. The internal command language must be reverse engineered as well.” In addition to having its own command language, it's also notable that the remote host can be a VMware VMCI target instead of a normal network address. “Taken as a whole, the approach here is consistent with a targeted, well-resourced operation rather than an opportunistic one,” Reichel wrote. The malware, hidden inside a 64-bit Windows DLL file, impersonates Microsoft's dpapi.dll, part of Windows' data protection API for protecting sensitive data. It exports the same seven functions as the real dpapi.dll, but attempts to forward calls to a file named dpapisvc.dll, which is not a real Windows component. The file also has a forged ESET Management Agent version resource, and loads via side-loading into ERAAgent.exe, the Windows executable for ESET Management Agent. After confirming that its host process is named ERAAgent.exe, Sleepwalker goes to sleep inside the computer's memory, which also helps it remain hidden from traditional anti-virus tools. Unlike most backdoors, which call back to an attacker-controlled command-and-control (C2) server and start receiving commands, Sleepwalker lies in wait, checking every packet that passes through the network looking for a specific pattern - this is called a magic packet. Once it sniffs out a packet that matches the exact pattern, the backdoor decrypts the data and treats it as a command. “Because the backdoor never sends anything out on its own and does not open any obvious listening port by default, tools that watch for connections to known-bad domains or unusual outbound traffic will not see anything unusual,” Reichel wrote. “The absence of outbound connections to known-bad infrastructure does not rule out an infection, either. A machine can be fully compromised by this backdoor while producing nothing at all for a network monitor to flag.” Hidden commands Every command sent to the backdoor is encrypted using AES-256-CCM, and the command language is unique in that, once decrypted, it is neither text nor a document. Instead, each command is a short sequence of raw bytes, and it only makes sense when read in a specific order. Reichel’s write-up includes a key that shows how to read the bytes, and each of Sleepwalker’s 23 instructions is written in this command language. Some of the instructions carry an inner program. For example, a scheduler can also contain a network listener, with a routine that waits for a particular file to be assembled and checked before it will run on the compromised computer. Beyond the two magic-packet sniffing instructions and basic instructions - such as an exit command that stops all running programs and the packet listener, and an instruction that starts a second, smaller program running concurrently with the parent program - the backdoor has multiple others. These include four instructions on sending and hiding data. One of these opens a TCP connection to a chosen address and port, and then sends a block of data to a remote host, which can be a VMware VMCI target instead of a normal network address. Another one writes a block of data to a Windows named pipe on a chosen computer, and can optionally log in with a username and password first. Five other instructions focus on inbound task reception, such as waiting to receive - or reaching out on its own - a follow-up instruction, opening a TCP or UDP port, or creating and/or connecting to a named pipe. Additionally, the malware has five different instructions on building and running programs. A lot of unknowns…and detection tools As Reichel notes, however, a lot remains unknown about Sleepwalker. “I have no collection context tying the file to a confirmed intrusion, so I cannot identify a victim, industry, country or affected organization,” he wrote. While we know that the DLL is designed to execute via side-loading after being placed beside ERAAgent.exe, we don't know how the malware operator first gained access to the computer or delivered the malicious file. We also don’t know the operator or developer, or what post-compromise activity, if any, took place. “I found no related code that would support attribution to a known group, and this one sample cannot establish when or how widely Sleepwalker was deployed, whether variants exist or whether it belongs to a continuing campaign,” Reichel wrote. Perhaps most importantly, for anyone who believes that they may be infected with Sleepwalker or a related malware sample, Reichel wrote, “I have created a toolkit to help decode its bytecode, examine encrypted and network artifacts, summarize behavior and indicators and safely reproduce its receiving pipeline without executing commands or transmitting traffic,” urging targeted individuals to contact him. He also created a mitigation guide, with a remediation script for use after Sleepwalker is detected.®
If you're curious how easily tech companies can fingerprint your browser and device and potentially single them out from the crowd, a new utility Glassbox will show you. Aside from pinging a public geolocation API, it runs entirely in a user’s browser and doesn’t ship any info out to the web while acting just like all the various trackers, anti-fraud scripts, and other browser fingerprinting tricks one is likely to encounter online. Unlike some other available tools that do the same, Glassbox provides a whole bunch of raw, unfiltered data you can sift through to see what makes your browser stand out, along with an estimate of how identifiable its fingerprint may be. In this vulture’s testing, Glassbox's estimate ranged from 99 percent in the Chrome window I use daily for work to a low of 56 percent in Tor Browser with an active circuit. “The ‘identifiability’ number is an honest model, not a measurement,” Glassbox developer David Dale said of his tool in a Hacker News thread. “It sums published per-signal entropy, discounts your browser masks, and caps at the ~33 bits needed to single out one person on Earth.” Dale added in the thread that, since it runs locally, that identifiability number is an estimate, as Glassbox doesn’t have a live population to pull against. AmIUnique and the EFF’s Cover Your Tracks, the other tools mentioned above, provide real population numbers, he noted. Dale got the idea for GlassBox after learning about silent sawtooth waves used by fingerprinting code found on Alibaba's AliExpress site to identify browsers using audio. Rather than fork one of the existing open source tools - both EFF's Cover Your Tracks and AmIUnique have GitHub repos - he decided to build his own, with some help from AI. “I'm a solo entrepreneur and long-time security engineer; tools like Claude Code have made it much easier to polish ideas and offer the useful ones to a wider audience,” Dale told us in an email. “I knew a fair number of fingerprinting methods but not that one, and I wanted to see all of them in one place, running against my own browser,” he said on Hacker News. In other words, Glassbox factors Alibaba’s tricks into its identifiability estimates alongside 30 other probes for unique browser data - things like canvas, WebGL, font libraries, WASM features, API matrices, and cross-site login states. According to Glassbox, my particular Chrome session I use for work is unique to around 1 in 7.6 billion browsers, and my IP address narrows that further (my ISP apparently uses IPv6, making me even more identifiable). As for which browsers appear to be safer, I have Safari, Edge, Firefox, and Tor on my machine alongside Chrome; Firefox and Tor are the only ones that didn’t label me “effectively unique,” giving me estimated identifiability ratings of 89 and 56 percent, respectively. What that means is that I share the same fingerprint as 1 in 681 million Firefox users and 1 in 408 thousand Tor users - that still doesn’t exactly make me a ghost online, but it definitely puts me in a pool much larger than Chrome, Edge, or Safari. Again, those are estimates, Dale reminded us, not a hard truth as, he says, “a no-server tool [can’t] measure true rarity.” “The single highest-impact move is to use a browser that puts you in a large, identical crowd,” Dale explained in an email. “Counterintuitively, a heavily customized ‘hardened’ setup often makes you more identifiable, because almost nobody else looks exactly like it. Blending in beats standing out.” Aside from using a browser that does a good job of obfuscating its user, Dale said a VPN or Tor is a must, as is finding a way to close the WebRTC leak that has long dogged internet users and leaves browsers identifiable through some VPNs thanks to being enabled by default in most web browsers. Glassbox includes a page of suggestions for how to anonymize yourself online, and let’s face it: With everything from invisible pixels to silent sound waves doing their damndest to figure out who’s behind a browser in order to make money off them, that’s more important than ever. ®
Cybersecurity researchers have found that several websites are still actively distributing a malware family known as Weedhack to gamers by masquerading as Minecraft clients.
McAfee Labs said it detected and blocked more than 6,300 attempts to access malicious sites, adding that it found lookalike gaming websites designed to mimic legitimate projects, including branding, feature lists, FAQs,
A suspected Iran-linked cyberattack shut down a small UK power plant around the time that a series of digital intrusions disrupted American water utilities across 12 states. A British government spokesperson confirmed the hack to The Register on Monday and told us that the security incident affected a “small-scale energy generator.” “At no point was there a risk to the wider energy system,” the spokesperson said, adding that the UK’s energy system is “highly resilient,” and that the government works “closely with the energy sector to protect infrastructure.” In a series of xeets about the cyberattack, UK Energy Minister Michael Shanks said that his department briefed energy CEOs after the incident and “shared further advice with companies on the steps they should take to stay secure.” Government officials did not disclose which power station shut down, and the UK has not formally attributed the cyberattack to Iran - or any other government or hacking group. The Telegraph, which first reported the news, said that the incident shut down the power plant for four days in what is believed to be the first disruptive Iranian cyberattack of its kind in the UK. In late July, suspected Iranian cyber operatives disrupted more than 30 water facilities in Minnesota, with similar intrusions subsequently reported across at least 11 other US states. While neither state nor federal officials have attributed these hacks to Iran, private-sector threat analysts have told The Register that Iran is “almost certainly” behind these breaches, which are a direct response to the ongoing Middle East conflict. While these earlier water-system intrusions didn’t appear to have an AI assist - most or all of the American utility cyberattacks involved internet-connected programmable logic controllers (PLCs) - last week the feds warned that attackers are now using AI-generated exploitation scripts to break into internet-exposed Siemens S7 Series PLCs at water, manufacturing, energy, and other critical facilities. “This is not a theoretical risk – it is an active threat,” the FBI and four other federal agencies warned. “This appears to be a continuation of the same suite of activity we suspect is affiliated with Iran targeting PLCs,” Cynthia Kaiser, Halcyon Ransomware Research Center SVP and a former FBI cyber analyst, told The Register. “Iran-affiliated actors and adversaries are actively targeting a wide swath of operational technology because these PLCs underpin essential health, safety, and critical infrastructure across society,” Kaiser said. ®
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