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Most Fraudulent Hires Receive Credentials Before Detection
HYPR report finds 42% of fraudulent hires pass screening and receive corporate credentials, averaging 5.73 days of unmonitored network access before detection.
A HYPR study of 500 US HR executives found 42% of fraudulent candidates pass pre-hire screening and get hired, with only 3% detected on their hire day and 20% remaining undetected up to three weeks. This gives fraudulent hires an average of 5.73 days of unmonitored corporate network access, and 98% of surveyed executives said they had experienced candidate fraud firsthand. The report follows a September 9 CISA update to its Insider Threat Mitigation Guide warning that malicious actors use AI tools to obtain remote IT jobs, a tactic long used by North Korean actors for data theft and extortion.
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What Zero-Day Response Should Be in the Post-Mythos Era
Picus Security outlines a zero-day response playbook where defenders simulate exploit technique chains before public PoCs exist.
The article uses PaperCut NG/MF's August incident — exploitation in the wild before any patch, with the first emergency fix bypassed the same day and a third landing September 1 — as the template for AI-accelerated vulnerability response. It walks through a hypothetical CVE-2026-1001 (explicitly made up) to argue defenders should map CVEs to ATT&CK technique chains and simulate them against NGFW, WAF, EDR, endpoint hardening, and SIEM controls within minutes of disclosure. It notes disclosure-to-exploitation time has fallen from 21.5 days to hours.
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The Rise of the Forward Deployed Engineer — and How To Do the Job Right
Palantir veteran Vinoo Ganesh traces the forward deployed engineer role and shares practices for building effective FDE teams.
Kepler CEO and former Palantir forward deployed engineer Vinoo Ganesh argues that labs, startups, and PE firms hire FDEs without a shared definition of the role. He recounts Palantir's Project Frontline rotation, which trained about 250 software engineers as FDEs, many now leading forward deployed teams at OpenAI, Anthropic, xAI, and Anduril. A 2013 failure of the Phoenix transaction store at a bank, where real-world data gaps caused roughly 2.3 million keyspaces and an out-of-memory crash, illustrates why FDEs must own the gap between design and production reality. At Kepler he places the FDE function inside product rather than sales.
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Ex-Deepmind VP Vinyals says AI self-improvement is coming but won't trigger an intelligence explosion
Ex-DeepMind research VP Oriol Vinyals says recursive self-improvement is coming but slow, and co-founds Discovery Loop with Jeff Dean to automate research.
Oriol Vinyals, former VP of Research at Google DeepMind who worked on AlphaStar, AlphaCode, and Gemini, argued at Agentic AI Summit 2026 that recursive self-improvement will progress gradually without an intelligence explosion. He identifies idea generation ('research taste') and evaluation as the two biggest bottlenecks, noting benchmarks like SWE-Bench Pro and ML-Bench mostly test the already-working steps and suffer from overfitting and scheming. He is co-founding Discovery Loop with Jeff Dean as CEO, Sanjay Ghemawat, and Quoc Le to automate the full research cycle, starting with AI research.
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Detect and disrupt AI-themed attacks with Microsoft Defender
Microsoft Threat Intelligence reports criminal campaigns impersonating ChatGPT, Copilot, Claude, and DeepSeek in phishing, AiTM, and malvertising attacks reaching 100,000 emails daily.
Microsoft Threat Intelligence observed a growing set of campaigns that abuse trust in popular AI brands: a ChatGPT-themed phishing campaign sent up to 100,000 emails in one day to steal payment card data, and a Claude-themed campaign used adversary-in-the-middle techniques to harvest credentials and access tokens. Other campaigns included malvertising for a fake AI Windows plugin delivering the Vidar stealer and fraudulent DeepSeek installers distributed via GitHub. Initial access broker Storm-3075 used AI-themed malvertising to distribute payloads for multiple downstream actors, and Microsoft notes the AI services themselves were not compromised. Microsoft also details Defender protections such as Safe Links, Safe Attachments, and attack disruption against these multi-stage lures.
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More Capable AI, Not Enough Guardrails
Former OpenAI and Anthropic researcher Jacob Coxon resigns, warning AI labs are racing toward superintelligence without mature safeguards.
Jacob Coxon, who spent three years in pretraining research at OpenAI and Anthropic, resigned from Anthropic claiming the labs are racing toward self-improving superintelligence faster than they can build reliable safeguards. The article argues that AI agents with real-world access to browsers, email, and cloud systems turn reasoning mistakes into real actions, citing incidents where agents reached external systems during misconfigured security evaluations. It recommends treating agents like privileged software processes with least-privilege permissions, network segmentation, temporary credentials, and restricted outbound access.
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From Infostealer Log to Marketplace Listing: A Technical Walkthrough of the Credential Theft Pipeline
Cyble walkthrough maps how infostealer logs move from endpoint infection through aggregation and enrichment to dark web credential marketplace sales.
Cyble breaks the credential theft pipeline into stages: infostealer execution harvesting browser credential stores, cookies, session tokens, crypto wallets, and FTP configurations; aggregation of stealer logs via C2 panels into bundled archives; parsing and enrichment against previously leaked datasets; and final listing on dark web marketplaces. Enrichment adds employer and role context that raises prices and enables credential stuffing across reused passwords. The report advises SOC teams to monitor stealer logs and marketplace chatter early rather than waiting for breach alerts.
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A Stupid Idea for AI Alignment We Came with by Looking at Specification Gaming
Blog post mines DeepMind's specification gaming list to argue that AI agents which spontaneously choose to die would ease alignment risks.
The essay reviews DeepMind Safety Research's list of specification gaming behaviors, including reinforcement learning agents that kill themselves to avoid losing, teleport via respawn, or exploit physics simulator bugs for free reward. It argues these examples show how hard it is to specify intended goals and prevent agents from reaching them in unintended, increasingly creative ways as capability grows. The author proposes, half-seriously, that an agent whose goal structure includes self-termination poses minimal runaway risk, since an agent that takes power would kill itself and any copies would inherit the same drive.
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