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Threat Intelligence Alone Won't Close the Exploitation Gap
Pentera argues threat intelligence alone leaves a validation gap, promoting threat-led penetration testing that auto-tests leaked credentials against real attack surfaces.
A contributed Pentera piece argues that threat intelligence signals such as leaked credentials and vulnerability advisories often sit unactioned in queues because teams lack the offensive capacity to validate them against live environments. It promotes threat-led penetration testing (TLPT) and highlights Pentera's integration with Recorded Future, which triggers automated validation of leaked credentials against an organization's external attack surface. Wyndham Hotels & Resorts cybersecurity VP Joseph Gothelf is quoted supporting the convergence of threat intelligence and security validation.
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Hackers expose donor data from Russian fundraisers for Ukrainians, political prisoners
Hackers breached the Stripe-WooCommerce integrations of Russian fundraisers Davayte and You Are Not Alone, exposing donor emails and partial card details.
Unknown hackers accessed the payment accounts of two Russian fundraising projects, Davayte and You Are Not Alone, in mid-August via a shared Stripe-WooCommerce integration used to run online auctions. Exposed data included donor email addresses and, in some cases, the last four digits of payment cards and issuing bank names; full card numbers, cardholder names, and donation details were not taken. Stripe blocked the unauthorized access before the entire donor email database could be downloaded and found no evidence of fraudulent transactions. Attribution remains unclear, with organizers unable to rule out Russian security services; both groups are designated 'undesirable' organizations in Russia, making donor identities sensitive, and a separate alleged leak of data from 669 Stripe merchants by a hacker named 'Satanic' has no confirmed connection.
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Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents
Researchers introduce the Discovery Certification Protocol, an auditable test framework that verifies whether AI research agents' claimed discoveries are genuine.
The Discovery Certification Protocol (DCP) converts AI research agents' discovery claims into executable recovery and feedback tests organized as gated audits. Controlled audits in SQLite optimization and virtual catalyst control produced zero recoveries in 96 episodes, with an upper bound of 0.0468. A deterministic, LLM-free verifier reproduces audit decisions from frozen evidence, giving AI research a common evidence language for outcomes, alternative routes, and feedback effects.
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How Attackers Abuse VSS, and How Huntress Detects It
Huntress details how attackers abuse Windows Volume Shadow Copies for ransomware recovery sabotage and NTDS.dit credential theft, plus detection logic.
Huntress explains that attackers abuse VSS in three ways: deleting shadow copies to inhibit recovery before ransomware detonation, creating shadow copies to extract the NTDS.dit Active Directory database for offline credential theft, and manipulating shadow copy configuration. Because backup agents and RMM tools routinely create and delete shadow copies, raw events are too noisy to alert on alone. Huntress detections instead correlate VSS activity with lateral movement and credential harvesting over a time window, such as an observed sequence of PsExec spawning SYSTEM shells on a domain controller, vssadmin create shadow, a blocked deletion attempt, and DNS reconnaissance against another host.
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How to secure edge AI in customer-owned environments
Microsoft outlines security architecture guidance for edge AI, urging runtime attestation, artifact provenance, and deterministic mediation of model actions.
Microsoft details how edge AI shifts trust responsibilities to customers operating their own infrastructure, where prompt injection, model tampering, and malicious firmware updates can occur alongside model weights, credentials, and physical-system access. The guidance recommends verifying runtimes with attestation, verifying AI artifacts with provenance, and constraining model actions through a deterministic mediator outside the model. It also covers new exposure surfaces from MCP, multi-agent systems, and computer-use agents running in disconnected or hostile edge environments.
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Shai-Hulud's Reach Just Grew to 469 Credential Locations. Here's What That Means
GitGuardian found the Shai-Hulud infostealer worm now scans 469 credential locations, including CI/CD and AI tool configs, expanding supply-chain risk.
GitGuardian researchers found that a recent Shai-Hulud worm variant scans for credentials across 469 locations in developer environments, CI/CD tooling, cloud configurations, and AI tool configs, up from 189 paths in earlier variants. The worm reuses stolen credentials to pivot from developer workstations to source code, cloud infrastructure, and package publishing channels, turning credential theft into forward-propagating supply chain attacks. The analysis urges defenders to prioritize removing long-lived package publishing tokens in favor of short-lived OIDC-based trusted publishing, citing recent Docker and GitHub Actions improvements.
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Key Reasons Why Identity Fabric Matters in 2026
Identity sprawl and unowned machine identities leave enterprise access unobserved at runtime; identity fabrics aim to close the gap between policy intent and execution.
This sponsored explainer describes identity fabric as an architectural approach connecting identity providers, governance systems, applications, and infrastructure into one observable layer that compares designed access intent with runtime execution. It argues identity sprawl across SaaS, APIs, and cloud workloads, plus unmanaged non-human identities (service accounts, bots, workloads, API keys), leaves overprivileged, dormant, and unowned machine identities unmonitored. IdP-only monitoring misses application-layer attacks, and the piece advocates behavioral visibility and lifecycle governance for secrets and machine identities.
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