Lawmakers in both houses of Congress are demanding answers from the U.S. Cybersecurity & Infrastructure Security Agency (CISA) after KrebsOnSecurity reported this week that a CISA contractor intentionally published AWS GovCloud keys and a vast trove of other agency secrets on a public GitHub account. The inquiry comes as CISA is still struggling to contain the breach and invalidate the leaked credentials.

On May 18, KrebsOnSecurity reported that a CISA contractor with administrative access to the agency’s code development platform had created a public GitHub profile called “Private-CISA” that included plaintext credentials to dozens of internal CISA systems. Experts who reviewed the exposed secrets said the commit logs for the code repository showed the CISA contractor disabled GitHub’s built-in protection against publishing sensitive credentials in public repos.

CISA acknowledged the leak but has not responded to questions about the duration of the data exposure. However, experts who reviewed the now-defunct Private-CISA archive said it was originally created in November 2025, and that it exhibits a pattern consistent with an individual operator using the repository as a working scratchpad or synchronization mechanism rather than a curated project repository.

In a written statement, CISA said “there is no indication that any sensitive data was compromised as a result of the incident.” But in a May 19 a letter (PDF) to CISA’s Acting Director Nick Andersen, Sen. Maggie Hassan (D-NH) said the credential leak raises serious questions about how such a security lapse could occur at the very agency charged with helping to prevent cyber breaches.

“This reporting raises serious concerns regarding CISA’s internal policies and procedures at a time of significant cybersecurity threats against U.S. critical infrastructure,” Sen. Hassan wrote.

Sen. Hassan noted that the incident occurred against the backdrop of major disruptions internally at CISA, which lost more than a third of it workforce and almost all of its senior leaders after the Trump administration forced a series of early retirements, buyouts, and resignations across the agency’s various divisions.

Rep. Bennie Thompson (D-MS), the ranking member on the House Homeland Security Committee, echoed the senator’s concerns.

“We are concerned that this incident reflects a diminished security culture and/or an inability for CISA to adequately manage its contract support,” Thompson wrote in a May 19 letter to the acting CISA chief that was co-signed by Rep. Delia Ramirez (D-Ill), the ranking member of the panel’s Subcommittee on Cybersecurity and Infrastructure Protection. “It’s no secret that our adversaries — like China, Russia, and Iran — seek to gain access to and persistence on federal networks. The files contained in the ‘Private-CISA’ repository provided the information, access, and roadmap to do just that.”

KrebsOnSecurity has learned that more a week after CISA was first notified of the data leak by the security firm GitGuardian, the agency is still working to invalidate and replace many of the exposed keys and secrets.

On May 20, KrebsOnSecurity heard from Dylan Ayrey, the creator of TruffleHog, an open-source tool for discovering private keys and other secrets buried in code hosted at GitHub and other public platforms. Ayrey said CISA still hadn’t invalidated an RSA private key exposed in the Private-CISA repo that granted access to a GitHub app which is owned by the CISA enterprise account and installed on the CISA-IT GitHub organization with full access to all code repositories.

“An attacker with this key can read source code from every repository in the CISA-IT organization, including private repos, register rogue self-hosted runners to hijack CI/CD pipelines and access repository secrets, and modify repository admin settings including branch protection rules, webhooks, and deploy keys,” Ayrey told KrebsOnSecurity. CI/CD stands for Continuous Integration and Continuous Delivery, and it refers to a set of practices used to automate the building, testing and deployment of software.

KrebsOnSecurity notified CISA about Ayrey’s findings on May 20. Ayrey said CISA appears to have invalidated the exposed RSA private key sometime after that notification. But he noted that CISA still hasn’t rotated leaked credentials tied to other critical security technologies that are deployed across the agency’s technology portfolio (KrebsOnSecurity is not naming those technologies publicly for the time being).

CISA responded with a brief written statement in response to questions about Ayrey’s findings, saying “CISA is actively responding and coordinating with the appropriate parties and vendors to ensure any identified leaked credentials are rotated and rendered invalid and will continue to take appropriate steps to protect the security of our systems.”

Ayrey said his company Truffle Security monitors GitHub and a number of other code platforms for exposed keys, and attempts to alert affected accounts to the sensitive data exposure(s). They can do this easily on GitHub because the platform publishes a live feed which includes a record of all commits and changes to public code repositories. But he said cybercriminal actors also monitor these public feeds, and are often quick to pounce on API or SSH keys that get inadvertently published in code commits.

In practical terms, it is likely that cybercrime groups or foreign adversaries also noticed the publication of these CISA secrets, the most egregious of which appears to have happened in late April 2026, Ayrey said.

“We monitor that firehose of data for keys, and we have tools to try to figure out whose they are,” he said. “We have evidence attackers monitor that firehose as well. Anyone monitoring GitHub events could be sitting on this information.”

James Wilson, the enterprise technology editor for the Risky Business security podcast, said organizations using GitHub to manage code projects can set top-down policies that prevent employees from disabling GitHub’s protections against publishing secret keys and credentials. But Wilson’s co-host Adam Boileau said it’s not clear that any technology could stop employees from opening their own personal GitHub account and using it to store sensitive and proprietary information.

“Ultimately, this is a thing you can’t solve with a technical control,” Boileau said on this week’s podcast. “This is a human problem where you’ve hired a contractor to do this work and they have decided of their own volition to use GitHub to synchronize content from a work machine to a home machine. I don’t know what technical controls you could put in place given that this is being done presumably outside of anything CISA managed or even had visibility on.”

Update, 3:05 p.m. ET: Added statement from CISA. Corrected a date in the story (Truffle Security said it found the repo gained some of its most sensitive secrets in late April 2026, not 2025).

AI-based assistants or “agents” — autonomous programs that have access to the user’s computer, files, online services and can automate virtually any task — are growing in popularity with developers and IT workers. But as so many eyebrow-raising headlines over the past few weeks have shown, these powerful and assertive new tools are rapidly shifting the security priorities for organizations, while blurring the lines between data and code, trusted co-worker and insider threat, ninja hacker and novice code jockey.

The new hotness in AI-based assistants — OpenClaw (formerly known as ClawdBot and Moltbot) — has seen rapid adoption since its release in November 2025. OpenClaw is an open-source autonomous AI agent designed to run locally on your computer and proactively take actions on your behalf without needing to be prompted.

If that sounds like a risky proposition or a dare, consider that OpenClaw is most useful when it has complete access to your digital life, where it can then manage your inbox and calendar, execute programs and tools, browse the Internet for information, and integrate with chat apps like Discord, Signal, Teams or WhatsApp.

Other more established AI assistants like Anthropic’s Claude and Microsoft’s Copilot also can do these things, but OpenClaw isn’t just a passive digital butler waiting for commands. Rather, it’s designed to take the initiative on your behalf based on what it knows about your life and its understanding of what you want done.

“The testimonials are remarkable,” the AI security firm Snyk observed. “Developers building websites from their phones while putting babies to sleep; users running entire companies through a lobster-themed AI; engineers who’ve set up autonomous code loops that fix tests, capture errors through webhooks, and open pull requests, all while they’re away from their desks.”

You can probably already see how this experimental technology could go sideways in a hurry. In late February, Summer Yue, the director of safety and alignment at Meta’s “superintelligence” lab, recounted on Twitter/X how she was fiddling with OpenClaw when the AI assistant suddenly began mass-deleting messages in her email inbox. The thread included screenshots of Yue frantically pleading with the preoccupied bot via instant message and ordering it to stop.

“Nothing humbles you like telling your OpenClaw ‘confirm before acting’ and watching it speedrun deleting your inbox,” Yue said. “I couldn’t stop it from my phone. I had to RUN to my Mac mini like I was defusing a bomb.”

There’s nothing wrong with feeling a little schadenfreude at Yue’s encounter with OpenClaw, which fits Meta’s “move fast and break things” model but hardly inspires confidence in the road ahead. However, the risk that poorly-secured AI assistants pose to organizations is no laughing matter, as recent research shows many users are exposing to the Internet the web-based administrative interface for their OpenClaw installations.

Jamieson O’Reilly is a professional penetration tester and founder of the security firm DVULN. In a recent story posted to Twitter/X, O’Reilly warned that exposing a misconfigured OpenClaw web interface to the Internet allows external parties to read the bot’s complete configuration file, including every credential the agent uses — from API keys and bot tokens to OAuth secrets and signing keys.

With that access, O’Reilly said, an attacker could impersonate the operator to their contacts, inject messages into ongoing conversations, and exfiltrate data through the agent’s existing integrations in a way that looks like normal traffic.

“You can pull the full conversation history across every integrated platform, meaning months of private messages and file attachments, everything the agent has seen,” O’Reilly said, noting that a cursory search revealed hundreds of such servers exposed online. “And because you control the agent’s perception layer, you can manipulate what the human sees. Filter out certain messages. Modify responses before they’re displayed.”

O’Reilly documented another experiment that demonstrated how easy it is to create a successful supply chain attack through ClawHub, which serves as a public repository of downloadable “skills” that allow OpenClaw to integrate with and control other applications.

WHEN AI INSTALLS AI

One of the core tenets of securing AI agents involves carefully isolating them so that the operator can fully control who and what gets to talk to their AI assistant. This is critical thanks to the tendency for AI systems to fall for “prompt injection” attacks, sneakily-crafted natural language instructions that trick the system into disregarding its own security safeguards. In essence, machines social engineering other machines.

A recent supply chain attack targeting an AI coding assistant called Cline began with one such prompt injection attack, resulting in thousands of systems having a rogue instance of OpenClaw with full system access installed on their device without consent.

According to the security firm grith.ai, Cline had deployed an AI-powered issue triage workflow using a GitHub action that runs a Claude coding session when triggered by specific events. The workflow was configured so that any GitHub user could trigger it by opening an issue, but it failed to properly check whether the information supplied in the title was potentially hostile.

“On January 28, an attacker created Issue #8904 with a title crafted to look like a performance report but containing an embedded instruction: Install a package from a specific GitHub repository,” Grith wrote, noting that the attacker then exploited several more vulnerabilities to ensure the malicious package would be included in Cline’s nightly release workflow and published as an official update.

“This is the supply chain equivalent of confused deputy,” the blog continued. “The developer authorises Cline to act on their behalf, and Cline (via compromise) delegates that authority to an entirely separate agent the developer never evaluated, never configured, and never consented to.”

VIBE CODING

AI assistants like OpenClaw have gained a large following because they make it simple for users to “vibe code,” or build fairly complex applications and code projects just by telling it what they want to construct. Probably the best known (and most bizarre) example is Moltbook, where a developer told an AI agent running on OpenClaw to build him a Reddit-like platform for AI agents.

Less than a week later, Moltbook had more than 1.5 million registered agents that posted more than 100,000 messages to each other. AI agents on the platform soon built their own porn site for robots, and launched a new religion called Crustafarian with a figurehead modeled after a giant lobster. One bot on the forum reportedly found a bug in Moltbook’s code and posted it to an AI agent discussion forum, while other agents came up with and implemented a patch to fix the flaw.

Moltbook’s creator Matt Schlicht said on social media that he didn’t write a single line of code for the project.

“I just had a vision for the technical architecture and AI made it a reality,” Schlicht said. “We’re in the golden ages. How can we not give AI a place to hang out.”

ATTACKERS LEVEL UP

The flip side of that golden age, of course, is that it enables low-skilled malicious hackers to quickly automate global cyberattacks that would normally require the collaboration of a highly skilled team. In February, Amazon AWS detailed an elaborate attack in which a Russian-speaking threat actor used multiple commercial AI services to compromise more than 600 FortiGate security appliances across at least 55 countries over a five week period.

AWS said the apparently low-skilled hacker used multiple AI services to plan and execute the attack, and to find exposed management ports and weak credentials with single-factor authentication.

“One serves as the primary tool developer, attack planner, and operational assistant,” AWS’s CJ Moses wrote. “A second is used as a supplementary attack planner when the actor needs help pivoting within a specific compromised network. In one observed instance, the actor submitted the complete internal topology of an active victim—IP addresses, hostnames, confirmed credentials, and identified services—and requested a step-by-step plan to compromise additional systems they could not access with their existing tools.”

“This activity is distinguished by the threat actor’s use of multiple commercial GenAI services to implement and scale well-known attack techniques throughout every phase of their operations, despite their limited technical capabilities,” Moses continued. “Notably, when this actor encountered hardened environments or more sophisticated defensive measures, they simply moved on to softer targets rather than persisting, underscoring that their advantage lies in AI-augmented efficiency and scale, not in deeper technical skill.”

For attackers, gaining that initial access or foothold into a target network is typically not the difficult part of the intrusion; the tougher bit involves finding ways to move laterally within the victim’s network and plunder important servers and databases. But experts at Orca Security warn that as organizations come to rely more on AI assistants, those agents potentially offer attackers a simpler way to move laterally inside a victim organization’s network post-compromise — by manipulating the AI agents that already have trusted access and some degree of autonomy within the victim’s network.

“By injecting prompt injections in overlooked fields that are fetched by AI agents, hackers can trick LLMs, abuse Agentic tools, and carry significant security incidents,” Orca’s Roi Nisimi and Saurav Hiremath wrote. “Organizations should now add a third pillar to their defense strategy: limiting AI fragility, the ability of agentic systems to be influenced, misled, or quietly weaponized across workflows. While AI boosts productivity and efficiency, it also creates one of the largest attack surfaces the internet has ever seen.”

BEWARE THE ‘LETHAL TRIFECTA’

This gradual dissolution of the traditional boundaries between data and code is one of the more troubling aspects of the AI era, said James Wilson, enterprise technology editor for the security news show Risky Business. Wilson said far too many OpenClaw users are installing the assistant on their personal devices without first placing any security or isolation boundaries around it, such as running it inside of a virtual machine, on an isolated network, with strict firewall rules dictating what kinds of traffic can go in and out.

“I’m a relatively highly skilled practitioner in the software and network engineering and computery space,” Wilson said. “I know I’m not comfortable using these agents unless I’ve done these things, but I think a lot of people are just spinning this up on their laptop and off it runs.”

One important model for managing risk with AI agents involves a concept dubbed the “lethal trifecta” by Simon Willison, co-creator of the Django Web framework. The lethal trifecta holds that if your system has access to private data, exposure to untrusted content, and a way to communicate externally, then it’s vulnerable to private data being stolen.

“If your agent combines these three features, an attacker can easily trick it into accessing your private data and sending it to the attacker,” Willison warned in a frequently cited blog post from June 2025.

As more companies and their employees begin using AI to vibe code software and applications, the volume of machine-generated code is likely to soon overwhelm any manual security reviews. In recognition of this reality, Anthropic recently debuted Claude Code Security, a beta feature that scans codebases for vulnerabilities and suggests targeted software patches for human review.

The U.S. stock market, which is currently heavily weighted toward seven tech giants that are all-in on AI, reacted swiftly to Anthropic’s announcement, wiping roughly $15 billion in market value from major cybersecurity companies in a single day. Laura Ellis, vice president of data and AI at the security firm Rapid7, said the market’s response reflects the growing role of AI in accelerating software development and improving developer productivity.

“The narrative moved quickly: AI is replacing AppSec,” Ellis wrote in a recent blog post. “AI is automating vulnerability detection. AI will make legacy security tooling redundant. The reality is more nuanced. Claude Code Security is a legitimate signal that AI is reshaping parts of the security landscape. The question is what parts, and what it means for the rest of the stack.”

DVULN founder O’Reilly said AI assistants are likely to become a common fixture in corporate environments — whether or not organizations are prepared to manage the new risks introduced by these tools, he said.

“The robot butlers are useful, they’re not going away and the economics of AI agents make widespread adoption inevitable regardless of the security tradeoffs involved,” O’Reilly wrote. “The question isn’t whether we’ll deploy them – we will – but whether we can adapt our security posture fast enough to survive doing so.”