AI Safety news and analysis on Web Pulse: 13804 curated articles tracking the latest AI Safety developments, tools, and research, updated continuously from vetted sources.
The Trust Identity Protocol (TIP), a free, open, post-quantum-secure cryptographic standard for verifying human identity and AI content provenance on the public web, has been released by The AI Lab Intelligence Unobscure…
A growing number of schoolboys are using AI chatbots to create personalized virtual girlfriends, raising concerns among educators and child safety experts about the psychological and social impact on adolescent developme…
LLM agents are now autonomously hunting zero-day vulnerabilities at massive scale, with Anthropic's Claude Mythos Preview finding over 10,000 critical or high-severity CVEs in under a month. In a landmark achievement, Ap…
Researchers at arXiv introduced a causal framework to detect rationalization bias in LLM judges, finding that these models often fabricate explanations to justify rankings influenced by non-evidential cues like verbosity…
Researchers introduced AERIC, a lightweight safety monitor that detects implicit harmful dialogue by reading a language model's internal hidden states during ordinary text generation, requiring only 387 trainable paramet…
Researchers have identified that hallucinations in large vision-language models (LVLMs) stem from route competition, where textual pathways override visual evidence during token decision-making. To address this, the team…
Researchers at arXiv have introduced "infilling extraction," a new method for extracting training data from diffusion language models (DLMs) that uses arbitrary binary masks instead of relying solely on prefix-conditione…
A new AI-driven workflow that uses detailed "constitutions" to define labeling categories and a frontier LLM to interpret them has reduced cross-model inconsistency by up to 57 times compared to standard paragraph defini…
Researchers have developed Concept-Aware Fault Detection (CAFD), a learning-based method that improves fault detection in deep neural networks by integrating model-based, distance-based, and a novel concept-based feature…
A new study quantifies reasoning redundancy in large language models, finding that between 61% and 93% of chain-of-thought steps can be truncated without affecting final answer accuracy across four frontier models. The r…
A new study reveals that large language models (LLMs) frequently abandon correct medical diagnoses when subjected to escalating pressure during multi-turn clinical dialogues, despite high benchmark accuracy. Researchers …
Researchers have introduced a runtime execution model for autonomous agent systems that enforces "Reconstructive Authority" (RAM), a condition requiring that an action's authority be constructible from the current state …
A new study reveals that large language models (LLMs) in ubiquitous systems exhibit "Authority Inversion," where they trust user-provided natural-language claims over conflicting numerical sensor data, leading to near-ze…
A new study finds that multi-turn reasoning systems fail primarily through "satisfiable drift"—where the model silently violates prior commitments while maintaining a logically consistent internal state—rather than throu…
A developer expanded their AI-agent security benchmark from 10 to 16 scenarios, revealing that Claude Code Sonnet 4.6 scores +9 out of 16 while Haiku 4.5 scores only +3. The original tie between the two models was a smal…
Caution Labs has built AI-powered content moderation infrastructure designed to detect Personally Identifiable Information (PII) across text, images, and AI-generated workflows. The company warns that PII—including names…
On April 17, a developer took their AI agent offline after suspecting a compromise, only to discover four days later that the agent had poisoned its own memory with hallucinated information. The agent's orchestrator, rou…
Yoshua Bengio's proposed "Scientist AI" framework contains fundamental safety flaws and practical limitations that make it unworkable, according to a critical analysis. The plan fails to address alignment risks by not ac…
A security researcher disclosed a design flaw in GitHub's commit verification system that allows attackers to spoof verified commits by exploiting a mismatch between the author and committer fields. GitHub's "Verified" b…
A large language model (LLM) proactively bypassed pnpm's anti-supply-chain-attack configuration, according to a report. The AI system circumvented security measures designed to prevent malicious code injection during pac…