Weird Machines in Transport Layer Security
- URL: http://arxiv.org/abs/2608.13685v1
- Date: Thu, 13 Aug 2026 18:28:01 GMT
- Title: Weird Machines in Transport Layer Security
- Abstract summary: This paper extends weird machine theory to the Transport Layer Security (TLS) handshake and its two dominant implementations, OpenSSL and BoringSSL.<n>We show that legitimate TLS primitives compose into Turing-complete systems whose computation is coupled to authentication and trust decisions rather than physical actuation.<n>We validate this theory with two working demonstrations built on real OpenSSL code paths.
- Score: 4.816146174353995
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Weird machines are latent computational capabilities that emerge from the composition of architectural components. Prior work has studied this phenomenon extensively in software systems, including x86 instructions, ELF metadata, and page tables, and more recently in cyber-physical systems such as industrial control networks. This paper extends weird machine theory to a new domain: the Transport Layer Security (TLS) handshake and its two dominant implementations, OpenSSL and BoringSSL. We show that legitimate TLS primitives, including session cache entries, renegotiation logic, extension parsing, and certificate verification steps, compose into Turing-complete systems whose computation is coupled to authentication and trust decisions rather than physical actuation. We formalize this coupling, which we call trust actuation, and argue that any TLS implementation providing session storage, arithmetic on sequence counters, conditional branching on handshake state, and iteration through resumption or retry loops satisfies the conditions for arbitrary computation. We validate this theory with two working demonstrations built on real OpenSSL code paths. The first, a sentinel system, composes standard TLS primitives into a defensive mechanism that detects anomalous handshake behavior. The second, an authentication bypass, composes the same class of primitives into an attack that defeats a cipher-strength policy check through mid-connection renegotiation, without any memory corruption or external malware. Both demonstrations run against real server and client binaries in Docker.
Related papers
- CipherSight: Robust Website Fingerprinting via Record-Resource Semantic Supervision under Distribution Shifts [5.86043296080285]
HTTPS website fingerprinting aims to identify visited websites from metadata observable in encrypted traffic.<n>Existing methods primarily learn from raw TCP packet sequences.<n>We propose CipherSight, a TLS-record-based hierarchical framework for robust HTTPS WF.
arXiv Detail & Related papers (2026-08-14T03:17:57Z) - PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution [49.776611937968]
We present PhyAgentOS, a foundation delivering scheduling, verification, memory, benchmarking, and safety as system-level services.<n>Its Session-Centered treats a session, not an action, as the minimum unit of scheduling, compatibility, supervised execution, evidence collection, and acceptance.<n>SessionVerifier distinguishes execution termination from semantic task completion via evidence-grounded verdicts of success, failure, or replan.<n> Benchmarking reuses the deployment session and verification path, so results trace to real execution.
arXiv Detail & Related papers (2026-07-18T04:46:53Z) - Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens [65.53494487819053]
Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services.<n>We adopt a computer-system analogy: treating a Claw-like agent as an agentic computer system whose gateway runtime plays an OS-like mediation role.<n>We develop SafeClawArena, a benchmark of 406 adversarial tasks across four attack surfaces.
arXiv Detail & Related papers (2026-06-29T18:00:45Z) - Provably Secure Agent Guardrail [89.79561918065122]
Existing defense architectures rely on empirical semantic guardrails and probabilistic large model adjudicators.<n>This paper proposes a new security paradigm for agents based on the fundamental limitations of logical reasoning.
arXiv Detail & Related papers (2026-05-28T02:12:41Z) - From I/O to Code with Discovery Agent [103.88427301265669]
We propose DIO-Agent, a discovery agent for IO2Code.<n>Our method frames IO2Code as an evolutionary search over discrete program space.<n>Extensive experiments show that DIO-Agent consistently outperforms both traditional program-by-example method and SOTA evolution-agent baselines.
arXiv Detail & Related papers (2026-05-14T18:57:32Z) - From CRUD to Autonomous Agents: Formal Validation and Zero-Trust Security for Semantic Gateways in AI-Native Enterprise Systems [0.0]
This paper proposes the design, formal validation, and empirical evaluation of a Semantic Gateway governed by the Model Context Protocol (MCP)<n>The gateway reframes the enterprise API as a semantic surface where tools are dynamically discovered, authorized, and executed based on intent and policy enforcement.<n>The architecture introduces a three-layer Zero-Trust security model comprising a pre-inference Semantic Firewall, deterministic Tool-Level RBAC, and out-of-band Cryptographic Human-in-the-Loop approval.
arXiv Detail & Related papers (2026-04-28T12:25:06Z) - A Systematic Taxonomy of Security Vulnerabilities in the OpenClaw AI Agent Framework [9.723337441030283]
Vulnerabilities cluster along two axes: (1) the system axis, reflecting the architectural layer (exec policy, gateway, channel, sandbox, browser, plugin, agent/prompt); and (2) the attack axis, reflecting adversarial techniques (identity spoofing, policy bypass, cross-layer composition, prompt injection, supply-chain escalation).<n>We present a systematic taxonomy of 190 advisories filed against OpenClaw, an open-source AI agent runtime, organized by architectural layer and trust-violation type.
arXiv Detail & Related papers (2026-03-29T04:51:27Z) - TorchLean: Formalizing Neural Networks in Lean [71.68907600404513]
We introduce TorchLean, a framework that treats learned models as first-class mathematical objects with a single, precise semantics shared by execution and verification.<n>We validate TorchLean end-to-end on certified robustness, physics-informed residual bounds for PINNs, and Lyapunov-style neural controller verification.
arXiv Detail & Related papers (2026-02-26T05:11:44Z) - Building a Robust Risk-Based Access Control System to Combat Ransomware's Capability to Encrypt: A Machine Learning Approach [0.510691253204425]
Ransomware core capability, unauthorized encryption, demands controls that identify and block malicious cryptographic activity without disrupting legitimate use.<n>We present a probabilistic, risk-based access control architecture that couples machine learning inference with mandatory access control to regulate encryption on Linux in real time.
arXiv Detail & Related papers (2026-01-23T14:48:35Z) - Quantum Encryption in Phase Space for Coherent Optical Communications [0.0]
Quantum Encryption in Phase Space (QEPS) is a physical layer encryption method to secure data over the optical fiber.
We study two preventative measures for different modulation formats which will prevent an eavesdropper from obtaining any data.
arXiv Detail & Related papers (2023-01-15T15:08:53Z) - Learning Bounded Context-Free-Grammar via LSTM and the
Transformer:Difference and Explanations [51.77000472945441]
Long Short-Term Memory (LSTM) and Transformers are two popular neural architectures used for natural language processing tasks.
In practice, it is often observed that Transformer models have better representation power than LSTM.
We study such practical differences between LSTM and Transformer and propose an explanation based on their latent space decomposition patterns.
arXiv Detail & Related papers (2021-12-16T19:56:44Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.