security auditors

Abstract: We certify an honest-decapsulation failure upper bound for ML-KEM-768 in an explicit random-function/centered-binomial (ROM/CBD) abstraction. Domain-separated public-matrix streams are modeled as independent uniform ring elements and secret/noise polynomials as independent CBD2 primitives; this is not an information-theoretic statement about the fixed SHAKE instantiation of FIPS 203. Recent formal assessments identify rigorous justification of ML-KEM's heuristic decapsulation-failure scale as an open problem; within the explicit ROM/CBD abstraction studied here, we obtain a dependency-preserving certified upper bound at that scale. The analysis preserves dependencies induced by the public matrix and by both ciphertext-compression terms. Its terminal chain has three components: an exact graph-coupled full-ideal reference for the joint c_u/c_v residual; a proper-ideal bivariate Fourier transport whose rare |T|>=3 branch is closed by an exhaustive three-factor anti-concentration replay; and exact bit-specific FIPS decoding events followed only by a 256-coordinate union bound. A formal partial-Fourier lemma makes the spectral-to-total-variation step explicit. The reduced rational certificate satisfies Pr[K' != K] <= P_* <= 2^-164.81, with -log2(P_*) = 164.810716201343121.... The 164.81 threshold is exact but numerically tight: the certified exponent exceeds it by only about 0.0007162 bit, and 164.82 is not certified. The result is an upper bound for an arbitrary message fixed independently of the public and secret randomness, under honest encryption and decapsulation. It is not an exact DFR, not a fixed-SHAKE equivalence theorem, not a new IND-CCA reduction, and not an adaptive delta-correctness result.

Abstract: Full-duplex speech models accept user speech while generating responses, creating an underexplored attack surface. We introduce DuplexJail, which delivers fixed, request-independent spoken prompts through the user audio channel. We compare fixed-delay interruption after the harmful request ends with refusal-triggered interruption following a cue in the model's streaming text. Across four open-source models and 720 harmful requests from AdvBench and HarmBench, fixed-delay interruption raises whole-response attack success rates on AdvBench to 40.3% for PersonaPlex and 48.7% for PersonaPlex-RL, increases of +33.8 and +39.3 percentage points. The refusal-triggered policy reaches 35.6% and 48.6%, respectively, with all trials scored regardless of whether an interruption occurs. Selected conditions also increase FLM-Audio's harmful-response rate, while BayLing-Duplex shows decreases. These findings identify spoken interruption as a jailbreak attack vector and motivate evaluating safety throughout ongoing full-duplex interaction.

Abstract: Software reuse allows existing components and third-party libraries to be incorporated into new applications, but binary-only components can obscure their origins and implementations. Software composition analysis seeks to identify these reused components and trace their provenance, supporting dependency inventory, vulnerability assessment, and security auditing. For PLC applications, binary2source matching provides a core link in this analysis: given an opaque PLC binary artifact, retrieve its corresponding Structured Text (ST) source file from a collected source repository. However, this task is complicated by cross-platform compilation heterogeneity, the representation gap between PLC binaries and ST source code, and the granularity mismatch between recovered binary units and ST source files. This paper presents PLC-Bin2Src, a cross-platform binary2source matching framework for retrieving corresponding ST source files for binaries produced by CODESYS, GEB, OpenPLC v2, and OpenPLC v3. Platform-aware frontends construct comparable representations, and a shared backend equally combines control--data flow graph (CDFG), function call graph (FCG), and recovered-symbol similarities to rank source candidates. We evaluate PLC-Bin2Src on PLC-BEAD. Results show that PLC-Bin2Src achieves 95.89% Recall@1, 99.66% Recall@5, and an MRR of 0.9769 across four PLC platforms.