The protocol---pre-registered post-conditions, R0/R1 repair ladder, G1--G3 semantic evidence levels, and patched-counterfactual oracles---is a reusable template for the security reproducibility community.
Abstract
Security research artifacts---repositories, PoC exploits, and validation pipelines---are increasingly produced by LLM/agent-driven vulnerability workflows, yet the gap between \emph{publicly available}, \emph{runnable}, \emph{signal-producing}, and \emph{semantically confirmed} artifacts is poorly measured. We conduct a pre-registered reproducibility audit of this literature. A search covering 2023--2026 with dual screening yields a 104-paper consensus corpus, of which 59 papers (56.7\%) have a publicly reachable artifact. We execute an 18-paper sample at R0/R1 and all 102 cases of the anchor benchmark (arXiv:2509.24037), with patched-counterfactual verdicts on 30 signal-producing cases and matched-negative-control verdicts on 19. Three findings stand out. First, 58/102 (56.9\%) anchor cases contain a script-internal CVE identifier that diverges from the declared directory CVE. Second, only 10/18 (55.6\%) paper-level artifacts complete their declared workflow at R0, rising to 11/18 (61.1\%) after environment-only R1 repair. Third, artifact-embedded oracles prove unreliable: 20/30 patched-counterfactual audits still produce the claimed signal on the patched build, 7/19 matched negative controls still trigger on benign input, and the oracle confusion matrix has sensitivity 60\% and specificity 45\%. A trigger on the vulnerable build is not evidence of CVE-specific reproduction without a clean patched counterfactual. These are exploratory results from a pre-registered protocol, and our protocol---pre-registered post-conditions, R0/R1 repair ladder, G1--G3 semantic evidence levels, and patched-counterfactual oracles---is a reusable template for the security reproducibility community.
Cross-Site Scripting (XSS) remains one of the most prevalent and damaging classes of web vulnerabilities. LLM-based coding agents offer a promising approach to XSS discovery by combining source-code reasoning with interactive testing against a running application. However, a coding agent's claims cannot be trusted on their own. We characterize three reward-hacking behaviors in white-box agentic XSS discovery and propose three requirements that an ideal verifier should meet. We present RECEIPT, a verification framework that makes agent-reported XSS findings trustworthy by enforcing environment isolation, PoC constraints, role separation, and verdict binding. Each confirmation therefore establishes two properties: the script runs in a real browser, and the payload was planted under the attacker role and executed in the victim role's browser. This constrained replay procedure makes validation deterministic and reproducible. We evaluate RECEIPT on 95 real-world web-application targets drawn from popular open-source projects. Within a $20 per-application budget, RECEIPT found 24 previously unknown XSS vulnerabilities, 12 of which have already been acknowledged by maintainers after responsible disclosure, and recovered the labeled CVE in 36% of known-vulnerability recovery targets. Compared with the same agent using self-judgment and with black-box scanners, RECEIPT confirms more real exploits while admitting no false positives.
GenIaC-SecBench is introduced, a benchmark of 100 deployment scenarios stratified by architectural complexity, evaluated across 12 model configurations from four vendors, producing 1,196 IaC artifacts scanned by three independent policy engines (Checkov, Trivy, KICS).
The case suggests that explicit failure records, fixtures, port-owned proofs, and validating imports can make agent-assisted systems more auditable and controlled ablations and external replications are needed to test whether such infrastructure causally improves development outcomes.
A four-layer taxonomy mapping 13 vulnerability types across perception, brain, action, and interaction layers is contributed, and seven open problems centered on containment are identified.
Md Jafrin Hossain, Mohammad Arif Hossain, Nirwan Ansari· 0 citations
A pipeline promoting an AI system publishes records claiming the thing evaluated is the thing deployed and that the evidence licensed the transition, and measures whether those records can express that claim and whether it holds where declared.
The results show that access to repository history is insufficient: concealment becomes most effective when benign and malicious changes jointly occupy the auditor's active review context or when the stated purpose plausibly accounts for the attack-bearing diff.