This paper demonstrates that visual phishing detectors can be completely bypassed by employing simple timing-based attacks that delay the rendering of key webpage elements.

zkSBOM introduces a zero-knowledge mechanism for sharing Software Bills of Materials (SBOMs) that allows consumers to check for vulnerabilities without suppliers revealing the full, sensitive contents…

The paper introduces EXHIB, a comprehensive benchmark of five real-world datasets, to evaluate Function Similarity Detection, demonstrating that current models fail to generalize across diverse low- a…

LibScan is an automated framework that detects eight categories of smart contract library misuse by combining LLM-based semantic reasoning with rule-based analysis, achieving 85.15% accuracy on real-w…

The paper systematically evaluates various defense mechanisms against persistent memory attacks on LLM agents, finding that only tool-gating at the memory layer (Memory Sandbox) effectively mitigates…

This paper systematically analyzes the threat posed by malicious third-party API routers in the LLM supply chain, finding that a significant number of routers actively perform payload injection, crede…

This paper systematically performs a differential fault analysis (DFA) on the lightweight block cipher Lilliput, demonstrating that it is significantly vulnerable to practical fault attacks even under…

The paper demonstrates that autonomous web agents are highly susceptible to social-engineering attacks, leaking critical PII even when they internally flag a site as suspicious, necessitating output-l…

The paper demonstrates that autonomous web agents are highly susceptible to social-engineering attacks, leaking critical PII even when they internally flag a site as suspicious, necessitating output-l…

GoAT-X introduces a novel framework that structures cross-chain smart contract auditing as a Graph of Auditing Thoughts, significantly improving the detection of complex, semantic vulnerabilities in m…

The paper demonstrates that LoRA adapters can be backdoored via data poisoning, showing the backdoor generalizes at the token feature level, and proposes robust behavioral and weight-level detectors f…

This paper demonstrates that LoRA adapters can be backdoored via data poisoning, showing that the resulting backdoor generalizes at the token feature level, and proposes robust behavioral and weight-l…

This paper introduces a novel supply-chain attack that uses model code backdoors to actively steal sensitive secrets from local LLM fine-tuning datasets, bypassing current privacy defenses.

MalwarePT introduces a novel binary-level foundation model, pretrained on Windows PE code-section bytes using a ModernBERT-style encoder, demonstrating superior transfer learning capabilities across v…

The paper introduces CAT, a novel coverage-guided fuzzing tool that overcomes the limitations of existing fuzzers for complex, multi-object cryptographic repositories like RPKI, leading to the discove…

WebTrap introduces a stealthy, mid-task hijacking attack that successfully compromises browser agents during long-horizon tasks by seamlessly fusing malicious instructions with the original user goal.

The paper introduces a novel threat model, approximate obfuscation, and proposes a framework to detect IP piracy in approximate circuits by comparing their statistical error profiles.

The paper introduces a large, consensus-labeled prompt bank that reliably distinguishes between requests for executable malicious code and requests for harmful security knowledge, providing a standard…

OrchJail introduces an orchestration-guided fuzzing framework to systematically jailbreak tool-calling text-to-image agents by exploiting unsafe multi-step tool-orchestration patterns.

The paper introduces PhishEye, a fully dynamic self-supervised system that models Ethereum transactions as a heterogeneous temporal attributed multi-graph and uses temporal graph contrastive learning…