2 links tagged with all of: supply chain attack + security
Click any tag below to further narrow down your results
Links
A developer leaked Anthropic’s real .claude folder containing 33 skills, a verifier subagent, and a seven-file harness. After integrating it locally, Claude stopped generating pointless tests and redundant confirmation prompts. The entire setup is now on GitHub with a one-line install script.
- A claimed "leaked" Anthropic internal .claude folder (33 skills, verifier subagent, 7-file harness) is being distributed via a one-line curl-to-bash install script on GitHub (Archive228/loopkit)
- Running curl-fsSL-piped-to-bash from an unverified repo to install unvetted "leaked" internal tooling is a significant security red flag, regardless of the productivity claims
- The claimed behavior changes (fewer test stubs, no false "done" markings, fewer confirmation prompts) are anecdotal and unverified, not benchmarked
- The framing pushes urgency ("bookmark before it disappears") which is a classic pressure tactic worth treating with suspicion rather than a substantive technical claim
The article discusses a recent supply chain attack involving the popular Axios package, highlighting how an attacker installed malware without altering the original code. It emphasizes the challenges posed by AI in both coding and attacking, as automated systems can easily introduce vulnerabilities faster than traditional security measures can respond.
- Attackers hijacked a maintainer account and slipped a self-deleting RAT into Axios (100M+ weekly downloads) via a malicious dependency, leaving no CVE for traditional scanners to catch.
- AI coding agents are 50% more likely than humans to pick known-vulnerable dependencies and often hallucinate package names that attackers exploit via "slopsquatting."
- Attacks have shifted from targeting single packages to automated, ecosystem-wide worms, like the TeamPCP campaign that spread through 66 npm packages in days.
- Socket detected the malicious Axios dependency in 6 minutes by analyzing code behavior, versus the industry-average 267 days for breach detection.