A low-stake adversary can degrade a liquid staking pool's performance via consensus manipulation and profit from the resulting drop in its LST value through application-layer financial positions.
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In: IEEE Symposium on Security and Privacy (S&P)
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PoisonCap uses a new poison capability format to deliver strict use-after-free and initialization safety for CHERI systems with no fundamental overhead over Cornucopia baselines.
An automated static-analysis pipeline generates labeled structural units from virtualization-obfuscated binaries so LLMs can analyze them without exceeding token limits.
Current AI image watermark removal attacks replace the watermark with a different forensic signal, allowing independent detectors to distinguish processed outputs from clean images at over 98% true-positive rate under a 1% false-positive budget.
GRASP detects anomalies in system provenance graphs via self-supervised executable prediction from two-hop neighborhoods, outperforming prior PIDS on DARPA datasets by identifying all documented attacks where behaviors are learnable plus additional unlabeled suspicious activity.
Pomegranate compartmentalizes commodity OS kernels via virtualization extensions, sentry functions, and EPT-enforced policies, achieving negligible overhead on a Linux network stack when compartment boundaries limit cross-talk.
Semia synthesizes Datalog representations of agent skills via constraint-guided loops to enable reachability queries for semantic risks, finding critical issues in over half of 13,728 real skills with 97.7% recall on expert-labeled samples.
BadStyle creates stealthy backdoors in LLMs by poisoning samples with imperceptible style triggers and using an auxiliary loss to stabilize payload injection, achieving high attack success rates across multiple models while evading defenses.
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.
PrivacyAkinator uses LLM-generated questions grounded in data-flow representations and a news-mined design space to help developers surface privacy decisions, yielding 47% more decisions identified in 73% less time than PRAM in a 24-person study.
ContentFuzz rewrites posts with LLM guidance from stance model confidence to flip machine labels without altering human intent, tested across four models and three datasets in two languages.
NanoTag enables byte-granular overflow detection on unmodified MTE binaries by combining hardware tagging with selective software tripwire checks on the Scudo allocator.
THREAT uses coordinated LLMs in an iterative optimization loop to generate jailbreak prompts that achieve higher success rates and lower detection rates than previous methods across tested models and datasets.
Roblox's automated chat moderation fails to catch numerous unsafe messages involving grooming, sexualization of minors, bullying, violence, self-harm, and sensitive information sharing, with users evading detection through various techniques.
The paper examines denial-of-service risks to multi-round transaction simulation arising from inter-transaction dependencies in smart-contract state.
StegoStylo achieves authorship obfuscation by steganographically altering 33% or more of words with zero-width characters, confounding stylometric systems.
Generative AI boosts attackers' ability to create harmful content at scale while also enabling defenders to detect threats, support users, and improve moderation processes.
The paper argues that agent security is best addressed as a systems problem by applying principles from operating systems, networks, and formal methods rather than relying solely on model robustness improvements.
A literature survey synthesizes 119 studies on AI-driven alert screening into a four-stage taxonomy of filtering, triage, correlation, and generative augmentation while identifying gaps in deployment realism and robustness.
A survey frames CPS resilience through five themes and illustrates them in connected transportation and medical systems to provide a roadmap for real-world resilience.
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PoisonCap: Efficient Hierarchical Temporal Safety for CHERI
PoisonCap uses a new poison capability format to deliver strict use-after-free and initialization safety for CHERI systems with no fundamental overhead over Cornucopia baselines.