Hackers Inject Credential-Stealer, RAT Into LiteLLM

Attackers compromised a version of LiteLLM this week by injecting malicious code into all seven of its published Python wheels on PyPI, delivering a package that included an infostealer to exfiltrate credentials and secrets and a remote access trojan (RAT) that could let bad actors run arbitrary code on infected machines. The compromised version –…

Jeff Burt Oct 23, 2026

Linux Foundation: AI Speeds Development, but Low-Quality Code Strains Maintainers

A new Linux Foundation study finds that generative AI is delivering big productivity gains for open source software developers, but AI is also creating an influx of low-quality code submissions that need time-consuming human review. The research found that an estimated 25% of incoming pull requests, which are proposed changes to software projects, are considered…

James Maguire Oct 22, 2026

Blogs

OpenAI Puts COBOL Migration to the Test, and Its Newest Models Mostly Pass

OpenAI’s latest coding benchmarks show substantial improvements in handling COBOL, Fortran and other low-resource languages. But for DevOps teams modernizing legacy applications, translating code is only half the challenge. The real test is preserving business logic, arithmetic precision and production behavior…

Tom Smith Oct 21, 2026

Survey: AI Coding Tools Increase Open Source Software Dependencies

A survey of 307 enterprise technology leaders finds that as organizations rely more on artificial intelligence (AI) coding tools to build applications, they are simultaneously increasing the amount of open source software they are dependent on. Conducted by the market research firm Moving Horizon on behalf of ActiveState, a provider of a platform for accessing…

Mike Vizard Oct 21, 2026

mabl Adds Harness to AI Testing Automation Platform

Mabl today extended its test automation platform with a harness that, in addition to enforcing guardrails and testing standards for artificial intelligence (AI) agents, enables application development teams to better understand the impact of code changes before a pull request (PR) is made. Announced at a mabl Experience event, the extensions to the test automation…

Mike Vizard Oct 21, 2026

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Ameya ChhatreOct 23, 2026

When 200 OK Isn’t OK: Observability for LLM Systems

Traditional monitoring can show an LLM-powered application as healthy even when it delivers incorrect answers. Drawing on experience at Varo Bank, this article explains why AI observability must go beyond the four golden signals and how automated evaluation, groundedness checks and CI pipelines can catch silent failures before they reach customers.

AI observabilityAI reliability