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Hackers Stole Flock’s Camera Software, Revealing How the Company Tracks Cars and People
Hackers who removed a Flock Safety license plate camera dumped its data, revealing person-detection capabilities and an encryption key stored unencrypted on the device.
A hacker collective calling itself stegan0gram physically removed a Flock Safety automatic license plate reader camera from a roadway, copied its storage, and shared the files with 404 Media, WIRED, and Distributed Denial of Secrets. Analysis found an encryption key in an unencrypted 'media' partition that unlocked videos of thousands of vehicle detections, with logs showing more than a million images generated in weeks. The software explicitly detects people, bicycles, and even bumper stickers, and records from one Georgia city were searchable by more than 2,000 agencies nationwide. The findings follow 2025 research by Jon Gaines documenting flaws enabling root-level access to Flock cameras.
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Autoencoder Is All You Need: Profiling and Detecting Malicious DNS Traffic
Palo Alto Unit 42 details an autoencoder-based method that profiles DNS traffic to detect C2 and malicious domains, blocking ~374,000 malicious DNS requests daily.
Unit 42 built an RNN-based autoencoder that compresses DNS traffic time series into fixed-dimensional 'DNS profiles' for each domain and device. Downstream classification, clustering, and anomaly detection modules flag suspicious domains, capturing 170 emerging suspicious domains in May 2024. Signatures block roughly 374,000 malicious DNS requests daily and run in the Advanced DNS Security service, with detections shared to Advanced URL Filtering. Case studies link DNS traffic patterns to C2 beaconing, dynamic DNS abuse, and DNS tunneling for data exfiltration.
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Understanding Angler Exploit Kit
Unit 42 examines Angler EK operations, including rapid zero-day adoption, fileless Bedep infections, and ransomware payloads like TeslaCrypt and CryptXXX.
Unit 42 published the second part of its Angler EK analysis, covering the kit's history since 2013, its SaaS rental model, and its focus on Flash, Internet Explorer, and Silverlight exploits. Angler integrated the CVE-2015-5119 Flash zero-day from the Hacking Team leak within hours and later added exploits for CVE-2015-2419 and CVE-2016-0034 roughly a month after Microsoft patched them. Campaigns use Angler to deliver ransomware such as CryptoWall, TeslaCrypt, and CryptXXX, plus banking trojans and stealers via EITest. Since August 2014, Angler has used fileless, in-memory execution, most often for Bedep, which later downloads CryptXXX and click-fraud malware.
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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.
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GPUThor: Amplifying Rowhammer Attacks via Non-Uniform Patterns to Exploit ECC-Protected GPUs
GPUThor uses non-uniform hammering to amplify Rowhammer on NVIDIA GPUs, achieving 500X-23,500X more bit flips and first exploits of ECC-protected GPUs.
GPUThor is a Rowhammer attack on NVIDIA GPUs that reverse-engineers memory-access coalescing behavior to enable non-uniform hammering patterns activating aggressor rows more intensely than decoy rows. By identifying refresh instances where in-DRAM mitigations apply, it constructs longer patterns that escape mitigation across refresh intervals. It yields 500X to 23,500X more bit flips than prior GPU Rowhammer attacks across NVIDIA A4000, A4500, A5000, and A6000 GPUs, and enables the first Rowhammer exploits on ECC-protected GPUs via uncorrectable double and triple bit flips, making denial-of-service and privilege-escalation attacks practical.
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HYDRA: Quantifying Botnet Resource Thresholds for Efficient Link-Flooding Attacks on LEO Satellite Networks
HYDRA models link-flooding attacks on LEO satellite constellations as botnet minimization, matching prior disruption with 34% fewer bots and 23% less traffic.
HYDRA formulates link-flooding attack variants against LEO constellations such as Starlink and Kuiper as botnet minimization problems, quantifying the smallest bot subset and traffic allocation needed to disrupt communications between targeted geographic areas. Under matched stealth constraints it matches the ICARUS attack's disruption using 34% fewer bots and 23% less aggregate traffic, sustaining over 97% attack success as topology evolves. The framework also evaluates five mitigations, including routing diversification, ingress policing, distance-based constraints, source throttling, and botnet attrition.
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Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection
Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.
Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.
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Omniscience for the Masses: New Threats in the Metaverse's Democratized World Creation
First systematic assessment of 25 metaverse platforms reveals five novel world-creation attacks enabling covert user surveillance on Roblox, Horizon Worlds, and VRChat.
Researchers present the first systematic security and privacy assessment of metaverse world creators, surveying 25 platforms that support user-created worlds. They designed and implemented five novel attacks that abuse standard creator tools to violate spatial, visual, and auditory constraints, enabling covert user surveillance and manipulation without software vulnerabilities or developer-level privileges. Five previously proposed attacks were replicated using only standard world-creation features. The authors conclude that existing platform vetting, runtime protections, and creator policies are insufficient to mitigate malicious world creators.
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Self-Verifying Anomaly Detection using Explainable AI for Cybersecurity of DER Networks
ExCYDER framework self-verifies anomaly detection alerts for DER power grids using LightGBM and SHAP, reaching over 98% detection accuracy.
The paper presents ExCYDER, an explainable AI anomaly detection framework for Distributed Energy Resource networks that combines LightGBM with SHAP to validate whether each model decision aligns with its feature-attribution evidence. On a realistic DNP3 dataset it achieved over 98% detection accuracy, 14.5 ms SHAP latency per alert, and confidence deviation within 5%. The self-verifying mechanism distinguishes coherent from inconsistent alerts, improving interpretability and auditability for DER-focused security operations centers.
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Heterogeneous Cross-Chain Transaction Tracing for Solana Bridges via Candidate-Set Selective Decision
SolTracer traces cross-chain transactions onto Solana bridges, improving open-world association F1 by 20.16% over the strongest baseline for illicit-fund tracing.
The paper formalizes four Solana-bound cross-chain transaction modes and proposes SolTracer, which maps heterogeneous execution semantics into a unified event space and uses candidate-set selective decision-making with abstention when valid targets are absent. In the challenging open-world setting with a 50% TA ratio, SolTracer improves F1 by 20.16% over the strongest baseline. An empirical study of real-world transfers examines count-value divergence across bridge mechanisms, cross-asset shifts, and decoupling between on-chain settlement and explorer visibility.
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Are Unreachable Nodes Truly Safe? Fully Eclipsing Monero's P2P Network!
Researchers present Nyx and Moros, the first eclipse attacks against Monero nodes behind NATs, requiring no inbound access and demonstrated on mainnet.
The paper presents the first eclipse attacks tailored to unreachable Monero nodes operating behind NATs, requiring no inbound access to the victim. The attacks poison the peerlists of reachable nodes, which relay contamination to unreachable nodes' whitelists, then exploit Monero's outbound connection refresh logic to evict benign neighbors and monopolize all outbound connections. Nyx achieves a complete, persistent eclipse of long-running unreachable nodes in large-scale SEED Emulator simulations, while Moros stealthily eclipses newly joined nodes during bootstrapping and was demonstrated on the Monero mainnet. Countermeasures are proposed.
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Meme Coin Factories: Uncovering Large-Scale Manipulations on pump.fun
Large-scale pump.fun study of 15 million meme coins identifies five manipulation classes including wash trading and a Market-Manipulation-as-a-Service ecosystem.
Researchers analyzed all 15 million coins launched on pump.fun over the last two years plus large random samples of transaction data, identifying five manipulation classes: wash trading, creator address obfuscation, coordinated sells, copycat coins, and social media manipulation. Strategic actors bypass the platform interface and implement strategies in a highly automated, low-latency way by interacting directly with the blockchain. The study also uncovers Market-Manipulation-as-a-Service (MMaaS) third-party tools that let non-technical users run these manipulations, and proposes mitigations for traders, pump.fun, and regulators.
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The Convergence of Space and Cyber: Evolving Threats in the Space Race 2.0
Recorded Future whitepaper warns nation-state cyber operations targeting satellites, ground stations and space supply chains will intensify during 'Space Race 2.0'.
Recorded Future's whitepaper argues that cyber operations will be decisive in the second space race, with espionage, destructive attacks, supply chain compromise and signal hijacking already affecting orbital assets and ground infrastructure. It predicts nation-states will extend cyber targeting toward deep-space ambitions such as lunar colonization and asteroid mining. The paper references the SPARTA adversarial framework and forums like Defence Space 24, and highlights US Space Command's integration of cyber and intelligence into space operations.
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NERVE Attacks: Breaking AI-Powered Brain-Computer Interfaces
Researchers characterize NERVE, five attack dimensions against AI-powered brain-computer interfaces, and release the EEGle framework uncovering 17 attack instances.
NERVE is a systematic attack class spanning the BCI stack across five orthogonal dimensions: Neuro-mimetic Forgery, Evasion via Desynchronization, Replay-based Hijacking, Vein Tapping, and Embedded Backdoors. The accompanying EEGle framework enables AI-assisted, extensible BCI security analysis and helped uncover 17 novel neuro-specific attack instances, revealing a stealth-effectiveness spectrum unique to BCI backdoor design. The authors show generative AI lowers the barrier to entry for non-expert attackers and release EEGle to the community.
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"Shut Up and Let Me Enjoy My Otome": Understanding and Measuring the Toxicity in Otome Game Communities
First large-scale study finds 22.20% of Weibo otome game posts toxic versus 3.71% on Reddit, with LLM detectors reaching 0.82 F1.
Researchers present the first large-scale measurement of toxicity in otome game communities, introducing OtomeSCAN, which collected and analyzed 620,045 posts from Weibo and Reddit over 18 months. They manually annotated 4,308 posts, identified eight target groups, and evaluated seven toxicity detectors, with their best LLM-based model reaching F1-scores of 0.82 on Weibo and 0.78 on Reddit. The study found 22.20% of Weibo posts were toxic versus 3.71% on Reddit, and toxicity rose to 37.09% within 72 hours during an external attack on Weibo. The authors also flagged 191 potential-coordination clusters, 64.40% of which targeted game developers.
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Identity-as-a-Service: Uncovering Dark Web Marketplaces Trading Executive SSNs
Rapid7 research uncovered dark web marketplaces trading executive Social Security numbers, fueling synthetic identity fraud and unauthorized lines of credit.
Rapid7 threat research documents dark web marketplaces where stolen executive Social Security numbers are bought and sold, a tier of the cybercrime ecosystem more durable than stolen payment cards because SSNs cannot be deactivated. Exposed SSNs enable unauthorized credit lines, synthetic identity fraud, and long-term impersonation. The article cites FTC statistics of over 1 million identity theft reports annually, with related fraud and imposter scams causing billions in losses each year.
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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.
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TLD Tracker: Exploring Newly Released Top
Unit 42 tracked 19 newly released top-level domains and found large-scale phishing, unwanted program distribution, and cybersquatting tied to TLD launch dates.
Researchers analyzed 19 new generic TLDs, including .zip, .bot, .ing, and .meme, released or approaching general availability over roughly 18 months. Data from passive DNS, registry zone files, newly registered domain feeds, and the Tranco top-1M list showed phishing campaigns, potentially unwanted program distribution, and domain squatting on these TLDs. Abuse correlated with each TLD's rollout phases, indicating attackers monitor general availability dates to register and weaponize domains. The IANA root database now lists over 1,000 generic TLDs.
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Beneath the Surface: Detecting and Blocking Hidden Malicious Traffic Distribution Systems
Unit 42 built an ML-based detector for malicious traffic distribution systems, finding malicious TDS chains average longer redirections and more URLs than legitimate ones.
Traffic distribution systems redirect victims through chains of intermediate domains to hide final destinations, serving phishing, malvertising, and online gambling operations. Unit 42's topological analysis of redirection graphs found malicious TDS traffic uses longer chains (about 25% exceed four hops vs 10% benign), more URLs (median 126 vs 80), and fewer isolated subgraphs with higher connectivity. These features power an ML detector integrated into Advanced DNS Security and Advanced URL Filtering to identify and block malicious TDS infrastructure in customer traffic.
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Almost Half of Malware Samples Communicate Direct to IP
Unit 42 analysis of 4 million malware reports finds 45% of C2-active samples connect directly to hard-coded IPs, bypassing DNS defenses.
Palo Alto Unit 42 analyzed over 4 million Advanced WildFire dynamic analysis reports and found that 45.32% of malware samples with C2 activity made at least one direct-to-IP connection, accounting for 23.17% of all C2 connection attempts. The firm proposes zero trust IP (ZT-IP), an enforcement approach that verifies whether outbound destinations were ever sanctioned by a DNS response. ZT-IP analysis surfaced Phorpiex ransomware droppers fetching payloads directly from C2 IPs, a persistent data exfiltration campaign using an obfuscated \GET protocol, and Mozi P2P botnet payloads delivered to IoT devices without DNS. Only 1% of benign samples connected directly to untrusted IP addresses.
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Harnessing LLMs for Automating BOLA Detection
Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.
Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.
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