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Risky Bulletin: Expired cards can be used for new transactions

Researchers show expired Visa contactless cards can be revived via NFC man-in-the-middle relay to run fraudulent transactions; roundup also covers major breaches.

University of Massachusetts Amherst researchers built an NFC man-in-the-middle rig that updates a card's expiration date in transit and relays the modified payment to POS terminals, reviving expired contactless cards; Visa terminals and the backends of all five banks studied failed to catch the manipulation. The same roundup reports Iranian hackers shut down a small UK power plant for four days, Lazarus breached South Korea's Presidential Office as part of a campaign exceeding 100 victims, and French telecom SFR suffered a breach affecting over 2.1 million customers.

Risky Business News · 24d agoResearch1

Domain-Incremental Learning for Multi-Channel Replay Speech Detection

First continual learning benchmark for multi-channel replay speech detection shows task-specific beamforming cuts catastrophic forgetting across 24 acoustic environments.

Researchers frame replay-attack detection for voice-controlled systems as domain-incremental learning over acoustic environments, evaluating a beamformer-based detector across all 24 environment orderings of the ReMASC corpus with five seeds. Naive sequential fine-tuning raises error rates on previously learned environments by 18.8 points, while elastic weight consolidation halves forgetting but loses plasticity and gradient projection memory is statistically indistinguishable from naive fine-tuning. A task-specific beamformer keeping one spatial front-end per environment significantly improves final and incremental accuracy, and the last environment in a sequence dominates final performance.

arXiv cs.CR · 6d agoResearch1

VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities

Introduces VEX-Bench, 75 expert-labeled real-world cases testing whether LLM agents can assess supply chain vulnerability exploitability; frontier models reach about 80% F1.

VEX-Bench is the first benchmark evaluating LLM agents on assessing whether upstream dependency vulnerabilities are exploitable in downstream projects, with 75 real-world expert-labeled cases across Python, Java, and Go mined from GitHub. Nine models across three agent harnesses were evaluated; GPT-5.5 and Claude Opus 4.6 reach approximately 80% F1 on binary vulnerability-status classification, but only GPT-5.5 surpasses 70% macro-F1 on fine-grained justification classification. The gap highlights the difficulty of moving beyond binary exploitability calls to explaining exploitability reasons, unlike prior benchmarks targeting zero-day settings.

arXiv cs.CR · 9d agoResearch1

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.

404 Mediaupdated · 7h agofirst · 19h agoResearch in the wild 3 sources

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security Labs · 1d agoResearch in the wild1

Illusion of Depth: Revealing Hidden Stereo Vision Vulnerabilities in Depth Estimation

Simple repeating patterns let attackers shift stereo-camera depth estimates by up to 20 meters, triggering emergency braking in autonomous driving frameworks at 40 km/h.

The paper reveals an intrinsic vulnerability in stereo cameras stemming from pixel sampling and calibration processes, letting attackers finely control estimated depth of real obstacles using simple repeating patterns without adversarial ML techniques. The attack was evaluated against BM and SGBM stereo matching algorithms, deep learning models PSMNet, MoCha-Stereo, and UniMatch, the stereo-LiDAR fusion model SGM-DDC, and commercial cameras ZED2 and Intel RealSense D435; on ZED2, obstacles can be displaced up to 20 meters farther or 12 meters closer. A 0.5-second attack triggered emergency braking in a popular autonomous driving framework, with feasibility confirmed at driving speeds up to 40 km/h using CARLA. State-of-the-art defenses proved ineffective, and the authors propose a similarity-score strategy to dynamically detect and suppress depth discrepancies.

arXiv cs.CR · 2d agoResearch

Private Information Retrieval With Arbitrary Privacy Requirements: Introduction and Capacity Results

Researchers formulate private information retrieval under arbitrary graph-based privacy requirements, deriving capacity bounds and introducing pyramid storage graphs.

The paper generalizes classical private information retrieval (PIR) to arbitrary privacy requirements over graph-based storage systems, where each message is retrieved privately from a pre-specified server subset. The authors derive lower and upper capacity bounds for general graphs and exact capacity results for path and cyclic storage graphs. They also introduce a new pyramid storage graph structure that models symmetric message storage and replication patterns.

arXiv cs.CR · 2d agoResearch

Phishing Research Challenges Conventional Security Awareness Testing

Pistachio's 2.47 million phishing simulations across 1,200 organizations show click rates alone mislead, with 30% of IT staff clicking and leak rates more predictive.

Between June 2025 and May 2026, Pistachio sent 2.47 million simulated phishing attempts to more than 123,000 employees at over 1,200 organizations, analyzing click, credential-leak and reporting behavior. Click rates ranged from 26% in Design to 41% in Construction; 30% of tech development and IT staff clicked at least once, while financial services were the most resilient sector. The report argues that click rate alone creates a false sense of security and that combined click, leak and report trends are better resilience indicators.

SecurityWeek · 5d agoResearch

Getting a stranger’s phone kicked off the cellular network costs a few dollars

Researchers show attackers can remotely block strangers' phones and alarm gateways on US cellular networks by abusing lost/stolen IMEI reporting for $2.50-$4 per device.

Researchers from Michigan State University and three partner schools found six weaknesses in the lost/stolen device reporting ecosystem spanning devices, carrier systems, and cross-carrier block-list sharing. They demonstrated blocking unopened Samsung Galaxy Z Fold 7 phones and home alarm gateways on three major US carriers, with each block costing $2.50-$4 and taking roughly 20-80 seconds. The attacks exploit thin identity and ownership checks in prepaid accounts, IMEI leakage from vulnerable cellular chipsets used by two vendors with over 40% global market share, and pre-release IMEI databases purchasable for $600. Victims receive no notification, and restoring service requires proving device ownership to the carrier.

Help Net Security · 6d agoResearch

On Identifying Adversarial Intent Injection in AI-Native 6G Networks

Dual-path CNN and AutoEncoder framework detects adversarial intent injection in AI-native 6G networks, reaching 0.97 accuracy and 0.98 F1.

The paper defines a fine-grained threat model for adversarial intent injection in AI-native 6G intent-based networking, where malicious policies are disguised within benign intent flows. It evaluates four injection strategies: stealth-mode, random distribution, increasing frequency, and decreasing frequency. A dual-path detection framework combines a CNN using TF-IDF features for supervised detection with an AutoEncoder trained only on benign data for one-class detection, reaching 0.97 accuracy and 0.98 F1-score, roughly 9% and 36% gains over the state-of-the-art baseline.

arXiv cs.CR · 6d agoResearch

Subgroup Membership Inference Audits of Differentially Private Synthetic Text

Audits of 32 differentially private synthetic-text releases show subgroup membership leakage is concentrated in few records and systematically underestimated by average-case attacks.

The paper defines a subgroup-targeted membership inference game in which the target pool is an explicit parameter, to audit residual leakage in differentially private synthetic text releases. The audit instantiates 32 proxies across four datasets, three generators (DP-SGD fine-tuning, API-based prompting, and activation steering), and five privacy budgets. DP substantially reduces average leakage at every budget, but remaining leakage is concentrated: roughly a tenth of records carries about 40% of it, and the noise removes more measured leakage from random records than from high-risk ones. Which records leak depends on the release mechanism, so record-level risk cannot be assessed independently of the release.

arXiv cs.CR · 7d agoResearch

Navigating the Latent Manifold: Proactive Concept Drift Adaptation for Resilient NIDS

Researchers propose DriftXpert, a concept-drift-adaptive network intrusion detection system validated on enterprise networks, addressing degraded AI-based NIDS performance in dynamic traffic.

AI-based network intrusion detection systems assume static data distributions and degrade under concept drift, raising false positives in dynamic environments. DriftXpert uses a two-stage offline framework: an unsupervised latent-manifold anomaly metric to detect traffic drift, and representation consistency alignment with cross-epoch neuron weight aggregation and selective freezing to transfer knowledge without catastrophic forgetting. Experiments on public datasets and a real enterprise network show effective adaptation to drifted data while retaining known-attack detection.

arXiv cs.CR · 8d agoResearch

Client-Side Probing of Deleted Ridge Statistics in Federated Unlearning

Researchers show malicious federated learning clients can probe broadcast classifiers to recover deleted samples, exposing exact label leakage on MNIST and CIFAR-10.

The paper shows that federated unlearning systems broadcasting updated linear classifiers leak compact additive training summaries to clients. A malicious client can submit known changes, identify server states from returned classifiers, and compare states around an isolated deletion to expose the deleted sample, class, or client summary, potentially enabling reinsertion. On MNIST and CIFAR-10, high-precision broadcasts allowed exact label recovery for every tested deletion, while lower precision sharply reduced fine-grained recovery.

arXiv cs.CR · 13d agoResearch

Your threat feed is someone else's database: What ingesting malware intel at scale takes

GitHub's Dependabot lead shares five production lessons for ingesting community malware intelligence feeds across eight package ecosystems at scale.

GitHub's Dependabot team monitors over 30 million repositories and extended malicious-package advisories from npm to eight package ecosystems by ingesting OpenSSF's malicious-packages intelligence. The team catalogued roughly 18 new malicious npm packages per day in the year ending May 2026. The write-up argues that provenance with batch reverts, fingerprinting to catch echo-chamber duplicates, and heavyweight normalization are the make-or-break engineering for feed ingestion. It also recommends automated publishing with import caps and anomaly flagging, and quarantining malformed records rather than silently repairing them.

Help Net Security · 14d agoResearch1

AI AppSec tools agree on just 5% of security findings

Contrast Security report finds 42 confirmed exploit attempts per application monthly and three AI scanners agreeing on only 5% of findings.

Contrast Security's AppSec Overflow 2026 report, drawing on telemetry from hundreds of thousands of production applications and APIs, found adversaries touch the average application every four minutes with 42 confirmed viable exploit attempts per application monthly, led by untrusted deserialization, path traversal, and method tampering. Legacy flaws Log4Shell and Spring4Shell remain widespread, mean time to exploit fell from over two years in 2018 to under three weeks for most 2025 exploited vulnerabilities, and average critical fix time is 92 days. Three AI scanners set on the same codebase agreed on only 5% of findings, and triaging a 2-million-line codebase scan cost roughly $128,000 versus $315 in API charges. Among exploited CVEs in the dataset, 82% of KEV-listed entries carried EPSS scores of 90% or higher, while CVE-2006-1547 and CVE-2023-38180 were confirmed exploited despite EPSS scores under 25%.

Help Net Security · 17d agoResearch in the wildCVE-2006-1547CVE-2023-381801

Can your coding style predict whether your code is vulnerable?

University of Massachusetts Dartmouth researchers present VulStyle, a stylometry-based vulnerability detector that also exposes benchmark reliability problems.

VulStyle combines stylometric features with syntax-tree structure and source tokens, pre-trained on about 4.9 million functions across seven programming languages and fine-tuned on five vulnerability detection datasets. It beat token-only detectors on some benchmarks but its F1 drops sharply on DiverseVul, which the authors link to noisy labels inflating reported performance across popular datasets. The authors argue style-aware detection should be harder to evade but did not test this empirically, and they note that uniform LLM-generated code may strip away the individual developer style the model depends on.

Help Net Security · 24d agoResearch1

Attack Paths Into VMs in the Cloud

Unit 42 maps attack paths into AWS, Azure, and GCP VMs through intended features like startup scripts and SSH key pushes.

Palo Alto Unit 42 reviewed attack vectors against virtual machine services on AWS, Azure, and GCP, finding that 11% of internet-exposed cloud hosts carry Critical or High severity vulnerabilities. The attack paths rely on legitimate features such as EC2 User Data, VM custom data, EC2 Instance Connect, SSM Run Command, and serial consoles rather than vulnerabilities, and exploiting them requires attackers to first obtain control plane permissions. A compromised VM exposes not only its data but the workload identity and cloud permissions assigned to it, making identity compromise potentially more damaging than data theft. The firm places mitigation responsibility on cloud users and administrators.

Palo Alto Unit 42 · Aug 17, 2026Research1

Hacking Public Wi-Fi DNS to Steal Credentials

Attackers can hijack public Wi-Fi DNS to redirect users to credential-stealing fake login pages; commenters debate HTTPS limits and mitigations like encrypted DNS.

The discussion examines how an attacker controlling DNS on shared or public Wi-Fi networks can redirect requests for legitimate services to attacker-controlled servers to steal credentials. Commenters analyze whether HTTPS and certificates mitigate the attack, noting attackers often rely on HTTP or browser trust quirks. Suggested defenses include encrypted DNS (DoH), DNSSEC, and travel routers running OpenWRT. No specific campaign, victims, or indicators are provided.

Schneier on Security · Aug 17, 2026Research1