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Anthropic Research
Sep 29, 2026
News
According to Anthropic, Zhipu AI's open-weight GLM-5.3 model builds complete exploits without serious guardrails against abuse.
In Anthropic's simulated tests, simple techniques bypass GLM-5.3's guardrails 64% to 100% of the time.
On ExploitBench, GLM-5.3 develops complete exploits in 50 attempts out of 410, against 56 for Claude Mythos Preview.
In one day, GLM-5.3 found several unknown flaws in a browser's JavaScript engine and chained them.
Abliteration takes GLM-5.3's refusal rate from more than 90% to about 3% on JailbreakBench.
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GLM-5.3 and the spread of advanced cyber capabilities
anthropic.com
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Blog Cloudflare
Sep 29, 2026
News
Cloudflare tested its own WAF with frontier AI models acting as a hacker.
The vast majority of attacks were blocked, with XSS, LFI, SQLi and Log4j near full coverage.
After human review, 49 findings were worth investigating, 48 of them CMDi and SSRF.
The work contributed to three changes in Cloudflare's Managed Ruleset, including two new SSRF detections.
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We tested our own WAF with frontier AI models. Here’s what we found
blog.cloudflare.com
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OpenAI Research
Sep 29, 2026
Release
OpenAI introduces dots, always-on AI agents powered by GPT-6 Astra.
Dots have their own cloud computer and can connect to over 4,000 apps through plugins.
Proactive research uses connected apps with tools restricted to be read-only.
Certain sensitive tasks, such as changing a password, always stay with the user.
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Introducing dots
openai.com
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Blog Cloudflare
Sep 29, 2026
News
Cloudflare develops CryptoLabe, an internal AI tool to spot the cryptography in its code before post-quantum migration.
The goal set is a complete post-quantum preparation for a target deadline in 2029.
The scans are done in two steps: a discovery of raw observations, then an analysis of each observation.
Without sufficient evidence, the model assigns More evidence needed, External dependency or Unknown rather than guessing.
No reference dataset yet allows reproducible comparison of the prompt versions.
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Using AI to chart a course for our post-quantum migration
blog.cloudflare.com
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Paolo Costanzo
Sep 29, 2026
Vulnerability
In six of the ten AI agent flaws examined, the model's judgement was never the decisive factor.
The ten disclosures, published between 26 June and 24 September 2026, are classified into four classes according to the trigger point.
In the other four cases, the model was manipulated, but permissions and configuration decided the extent of the damage.
GitSpawn groups eight findings in seven command-line agents, including Claude Code, Goose, Codex and Cursor.
A correction on 13 October brings the figure from seven to six, after the reclassification of CVE-2026-55607 (Claude Code).
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Outside the Prompt: What This Summer's AI Agent Vulnerabilities Have in Common
paolocostanzo.github.io
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