CyberIntel ⬡ News
★ Saved ◆ Cyber Reads
← Back ◬ AI & Machine Learning Apr 15, 2026

Tamper-Proofing with Self-Modifying Code

arXiv Security Archived Apr 15, 2026 ✓ Full text saved

arXiv:2604.12407v1 Announce Type: new Abstract: Classical computability theory tells us that self-modifying code (SMC) on a deterministic universal Turing machine can be simulated by non-SMC code on the same model. That abstraction, however, omits the external timing inputs, concurrency, and microarchitectural state that dominate practical execution on modern processors. We argue that once timing, ordering, and self-introspective effects are treated as observables, a practically faithful non-SMC

Full text archived locally
✦ AI Summary · Claude Sonnet


    Computer Science > Cryptography and Security [Submitted on 14 Apr 2026] Tamper-Proofing with Self-Modifying Code Gregory Morse, Tamás Kozsik Classical computability theory tells us that self-modifying code (SMC) on a deterministic universal Turing machine can be simulated by non-SMC code on the same model. That abstraction, however, omits the external timing inputs, concurrency, and microarchitectural state that dominate practical execution on modern processors. We argue that once timing, ordering, and self-introspective effects are treated as observables, a practically faithful non-SMC reproduction of timed SMC becomes detectably expensive on commodity systems. We present a tamper-proofing model that combines introspective and polymorphic SMC, reliable clocks, and runtime timing predicates to bind integrity checks to execution behavior. We distinguish static and dynamic SMC generation, characterize the timing semantics needed to avoid catastrophic pipeline clears, and give x86-64 design primitives for checksum-driven self-patching. We also report timer measurements, performance comparisons, and performance-monitoring counter evidence showing that careful engineering -- especially loop unrolling and cross-page modification -- substantially reduces the overhead of SMC while preserving its tamper-detection value. The paper concludes with an efficiency analysis, a threat model, and deployment guidance for trusted code executing in untrusted environments. Comments: 12 pages, 5 figures, 6 tables Subjects: Cryptography and Security (cs.CR) MSC classes: 68M25 (Primary) 68M20, 68N30, 68Q60 (Secondary) ACM classes: D.4.6; D.4.8; D.2.0 Cite as: arXiv:2604.12407 [cs.CR]   (or arXiv:2604.12407v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.12407 Focus to learn more Submission history From: Gregory Morse [view email] [v1] Tue, 14 Apr 2026 07:44:17 UTC (28 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
    💬 Team Notes
    Article Info
    Source
    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 15, 2026
    Archived
    Apr 15, 2026
    Full Text
    ✓ Saved locally
    Open Original ↗