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CategoryAllMalware 1278Vulnerability 1010Exploit / PoC 648Ransomware 628Threat actor 366Data breach 165Phishing & fraud 115Policy & legal 76Industry 61AI safety & security 33Research 29Advisory 25AI tools & infra 17Tools 17
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The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE

Unit 42 demonstrates that root access on a Kubernetes node lets attackers spoof SPIFFE/SPIRE attestation and harvest co-located workloads' SVIDs.

Palo Alto Networks Unit 42 describes post-exploitation techniques in which an attacker with root on a compromised Kubernetes node spoofs Linux cgroup metadata used by the SPIRE agent during workload attestation, tricking it into issuing a co-located workload's SPIFFE Verifiable Identity Document to an attacker-controlled process. The research shows the core trust assumption of machine-identity systems—that the node is trusted—collapses once root is obtained, exposing all cryptographic identities scoped to that node. Unit 42 released an open-source tool, Spooffe, for defenders to test identity exposure, and notes the technique has not been observed exploited in the wild.

Palo Alto Unit 42 · 6d agoResearch1

Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security Labs · 5d agoResearch

When the Whole Company Adopts AI: What It Does to Your SOC

Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.

A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.

The Hacker News · 4d agoResearch1

How to correlate Kubernetes audit logs with container runtime data

Elastic Security Labs shows how to join Kubernetes audit logs with Defend for Containers runtime data to investigate service account abuse and container escapes.

Elastic Security Labs demonstrates correlating Kubernetes audit logs with Defend for Containers (D4C) runtime telemetry in Elastic. In an Amazon EKS lab, a compromised workload service account performed discovery, read secrets, minted a token, created a privileged pod, and execed into it to attempt a container escape via nsenter and chroot. The escape wrappers appeared only in the decoded Kubernetes audit requestURI, not in runtime process events. The post covers join fields, prebuilt EQL sequence rules, and continues the control-plane correlation thread from the TeamPCP container attack scenario and the Hugging Face intrusion write-up.

Elastic Security Labs · 13d agoResearch1

Risky Bulletin: Academics find source code overlaps between Geedge and China's Great Firewall

Academics linked Chinese vendor Geedge Networks' Tiangou Secure Gateway source code to one of the Great Firewall's three traffic filtering capabilities.

US researchers presenting at USENIX Security reconstructed Geedge Networks' Tiangou Secure Gateway firmware from over 100,000 leaked files, including Git repositories with commit history, and matched its filtering behavior to sections of China's Great Firewall. They found only 1 of 3 characterized DNS injectors matched Geedge code, noted the system relies on memory-unsafe C components and copied third-party code, and said its bugs could aid future circumvention tools. Geedge also exports censorship tools to Kazakhstan, Ethiopia, Pakistan, and Myanmar. The newsletter additionally rounds up multiple breaches.

Risky Business News · 26d agoResearch2

Forgery of C2PA on a Pixel 10

Researcher forged a Google Pixel 10 C2PA content credential with genuine signatures, showing root-level attackers can fake photo provenance.

A Hacker Factor blog post demonstrates an AI-generated 'unicorn glitter milk' news photo carrying a valid, cryptographically signed C2PA manifest traceable to Google's Pixel camera certificate chain, passing validation in Adobe Inspect and the CAI Verify tool with a verified timestamp. The author, working with UMBC's PASAWG working group, reported to Google and C2PA in November 2025 that root access on a Pixel device could sign arbitrary images as camera captures; after 90 days without resolution, details were published. The finding undermines C2PA Assurance Level 2 claims made for Pixel 10 Content Credentials.

Lobsters · security · 8h agoResearch

Hackers Turn Windows Shadow Copies Into a Tool for Credential Theft and Ransomware

Attackers abuse Windows VSS shadow copies to delete recovery points before ransomware and to extract NTDS.dit/SAM credentials, demanding context-aware detection.

Threat actors are weaponizing the Volume Shadow Copy Service (VSS) for two purposes: destroying local recovery points via vssadmin.exe, wmic.exe, diskshadow.exe, wbadmin.exe, and bcdedit.exe before encryption, and accessing static copies of locked files such as NTDS.dit and SAM for credential theft. Ransomware families tied to shadow-copy removal include Akira, Black Basta, BlackCat, Conti, LockBit, Qilin, RansomHub, REvil, Ryuk, and WannaCry. Huntress's analysis of the Nightmare-Eclipse tool showed the BlueHammer technique chaining a Windows Defender timing issue with a VSS snapshot to dump the SAM database and decrypt NT hashes. Defenders should correlate VSS operations with parent process, hive access, and subsequent encryption activity, and maintain immutable off-host backups.

GBHackers · 1d agoResearch in the wild1

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.

Huntress · 2d agoResearch

New GPUThor Rowhammer Defeats ECC on NVIDIA RTX A6000 to Gain Host Root Access

University of Toronto researchers present GPUThor, a Rowhammer attack that defeats ECC on NVIDIA RTX A4000-A6000 GDDR6 GPUs and achieves host root access.

GPUThor uses non-uniform hammering to bypass Target Row Refresh and overcome SECDED ECC on NVIDIA Ampere workstation GPUs with GDDR6 memory, inducing 72,000 to 377,552 bit flips per gigabyte across RTX A6000, A5000, A4500, and A4000 cards. Triple-bit silent data corruption enables host privilege escalation to root with the IOMMU enabled, reusing GPUBreach page-table corruption techniques, and double-bit DUEs allow escalation when the IOMMU is disabled during a ~10 ms lazy-service window. The attack cut end-to-end escalation time on the A6000 from 21.9 hours to 1.1 minutes. Reported to NVIDIA, Google, Microsoft, and AWS on April 29, 2026; findings were embargoed until August 25, 2026, and no CVE identifier was assigned.

The Hacker News · 8d agoResearch1

Automobile Camouflage to Hide from Flock Cameras

Schneier on Security highlights a printed vehicle-camouflage pattern tested to defeat Flock surveillance cameras and Axon body cameras.

The post discusses covering cars with printed patterns designed to fool Flock automated license-plate recognition software, with testing reportedly done against Flock and Axon body cameras. Reader comments question effectiveness against other ALPR vendors, Flock's RF MAC-address upgrade, and whether such camouflage might become regulated. The page also contains off-topic comment threads about anti-bot over-blocking and privacy.

Schneier on Security · 9d agoResearch

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future · 21d agoResearch

The Gopher in the Room: Analysis of GoLang Malware in the Wild

Unit 42 analysis of 10,700 Go-compiled malware samples shows steady growth in the wild, with 92% targeting Windows and top families including Veil, GoBot2, and HERCULES.

Unit 42 collected roughly 10,700 unique Go-compiled malware samples and found that Go usage by malware developers has steadily risen in recent months. About 92% of samples targeted Windows and 75% were attributed to known families, led by Veil, GoBot2, and HERCULES. The most prevalent groupings were penetration testing tools, remote access Trojans, and backdoors. Statically linked Go binaries average 4.65MB, which can complicate phishing delivery but sometimes causes antivirus products to skip or fail scanning.

Palo Alto Unit 42 · Aug 17, 2026Research1