Trusting-Trust Attack against an Entire Linux Distribution through Binary Manipulation

• URL: http://arxiv.org/abs/2607.24888v1
• Date: Mon, 27 Jul 2026 12:59:15 GMT
• Title: Trusting-Trust Attack against an Entire Linux Distribution through Binary Manipulation
• Abstract summary: We show that Ken Thompson's trusting-trust attack is not a threat to specific compilers.<n>We construct a complete trusting-trust attack around strip, an ordinary build utility that neither inspects nor generates source code.<n>On a real nix dependencys revision, the attack builds a complete installer without failures and backdoors almost every one of its binaries.
• Score: 14.907770304518273
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Ken Thompson's trusting-trust attack, in which a compromised compiler backdoors the programs it builds and reproduces the backdoor in subsequent rebuilds of itself, is widely regarded as a threat specific to compilers. We show that it is not. We construct a complete trusting-trust attack around GNU strip, an ordinary build utility that neither inspects nor generates source code, using only manipulations of finished ELF files. In the bootstrap of the NixOS Linux distribution, a single tampered strip in the binary seed implants a payload that propagates from one generation of strip to the next and survives into the final standard environment after the seed leaves the dependency closure. On a real nixpkgs revision, the attack builds a complete graphical installer without failures and backdoors almost every one of its binaries, enabling arbitrary malicious behavior of the subverted packages.

Related papers

• HazardAuditor: From Executable Threats to Safer Computer-Use Agents [50.06351661912873]
  Existing guard models target static prompts and responses.<n>Existing safety platforms produce evaluation verdicts rather than the normalized supervision a guard model needs to learn.<n>We introduce HazardAuditor, an execution-grounded framework that closes both gaps.
  arXiv  Detail & Related papers  (2026-09-14T07:09:33Z)
• Not In My Git Yard: Catching Backdoors at Commit and Release Time [4.705824178814535]
  Code-level backdoors-stealthy code changes that grant hidden privileges via secret triggers-pose a persistent threat to opensource software.<n>Existing Continuous Integration (CI) pipelines cannot detect these attacks, and downstream binary analysis tools require substantial manual effort.<n>We present Lily, an automated approach that strengthens open-source development and release processes against backdoor injection.
  arXiv  Detail & Related papers  (2026-07-29T10:09:48Z)
• From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors [89.92617739143846]
  We introduce ClawTrojan, a benchmark designed to identify multi-step trojan attacks in local agentic harnesses.<n>We propose DASGuard, which scans control-like text in sensitive local files, traces its origin, and removes control content that does not originate from a trusted source.<n>Our results show that DASGuard achieves strong dynamic defense by combining runtime attack blocking with sanitized commits to the workspace.
  arXiv  Detail & Related papers  (2026-05-29T09:19:07Z)
• Patch2Vuln: Agentic Reconstruction of Vulnerabilities from Linux Distribution Binary Patches [3.93181912653522]
  This paper asks whether a language-model agent, restricted to local binary-derived evidence, can reconstruct the security meaning of Linux distribution updates.<n>Patch2Vuln is a local, resumable pipeline that extracts old/new ELF pairs, diffs them with Ghidra and Ghidriff, ranks changed functions, builds candidate dossiers, and asks an offline agent to produce a preliminary audit.<n>We evaluate Patch2Vuln on 25 Ubuntu.deb package pairs: 20 security-update pairs and five negative controls, all manually adjudicated against private source-patch and binary-function ground
  arXiv  Detail & Related papers  (2026-05-07T17:22:22Z)
• Verifiable Provenance of Software Artifacts with Zero-Knowledge Compilation [5.939983212292006]
  We propose a novel approach to verifiable provenance based on compiling software with zero-knowledge virtual machines (zkVMs)<n>By executing a compiler within a zkVM, our system produces both the compiled output and a cryptographic proof attesting that the compilation was performed on the claimed source code with the claimed compiler.<n>Our results show that zk-compilation is applicable to real-world software and provides strong security guarantees.
  arXiv  Detail & Related papers  (2026-02-12T12:36:36Z)
• Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models [62.87838888016534]
  Graph Foundation Models (GFMs) are pre-trained on diverse source domains and adapted to unseen targets.<n>Backdoor attacks against GFMs are non-trivial due to three key challenges.<n>We propose GFM-BA, a novel Backdoor Attack model against Graph Foundation Models.
  arXiv  Detail & Related papers  (2025-11-22T08:52:09Z)
• Context-Guided Decompilation: A Step Towards Re-executability [50.71992919223209]
  Binary decompilation plays an important role in software security analysis, reverse engineering and malware understanding.<n>Recent advances in large language models (LLMs) have enabled neural decompilation, but the generated code is typically only semantically plausible.<n>We propose ICL4Decomp, a hybrid decompilation framework that leverages in-context learning (ICL) to guide LLMs toward generating re-executable source code.
  arXiv  Detail & Related papers  (2025-11-03T17:21:39Z)
• Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers [28.679695741222318]
  Deep learning (DL) compilers are core infrastructure in modern DL systems.<n>Can an official, unmodified compiler alter a model's semantics during compilation and introduce hidden backdoors?<n>We study both adversarial and natural settings. In the adversarial case, we craft benign models where triggers have no effect pre-compilation but become effective backdoors after compilation.
  arXiv  Detail & Related papers  (2025-09-14T09:11:49Z)
• Reproducible Builds and Insights from an Independent Verifier for Arch Linux [0.0]
  Supply chain attacks have emerged as a prominent cybersecurity threat in recent years.<n>Reproducible and bootstrappable builds have the potential to reduce such attacks significantly.<n>In combination with independent, exhaustive and periodic source code audits, these measures can effectively eradicate compromises in the building process.
  arXiv  Detail & Related papers  (2025-05-27T18:14:36Z)
• Evil from Within: Machine Learning Backdoors through Hardware Trojans [51.81518799463544]
  Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars.<n>We introduce a backdoor attack that completely resides within a common hardware accelerator for machine learning.<n>We demonstrate the practical feasibility of our attack by implanting our hardware trojan into the Xilinx Vitis AI DPU.
  arXiv  Detail & Related papers  (2023-04-17T16:24:48Z)
• BackdoorBox: A Python Toolbox for Backdoor Learning [67.53987387581222]
  This Python toolbox implements representative and advanced backdoor attacks and defenses. It allows researchers and developers to easily implement and compare different methods on benchmark or their local datasets.
  arXiv  Detail & Related papers  (2023-02-01T09:45:42Z)

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.