QUANTA: A Quantum-Compute Threat Axis for Cross-Framework Verification Systems

Established threat-modeling frameworks contain no dedicated axis for quantum-compute threats. The individual threats are well studied, harvest-now-decrypt-later, Grover/Shor capability escalation, quantum side-channels, and circuit fingerprinting each have an active literature, but they are scattered across separate research communities and are not consolidated into a taxonomy usable within a standard data-flow threat-modeling process alongside STRIDE and LINDDUN. This work introduces QUANTA, a quantum-compute threat axis of seven categories (Q1 harvest-now-decrypt-later, Q2 superposition manipulation, Q3 cross-framework convergence attack, Q5 capability escalation, Q6 collapse side-channel, Q7 algorithm identification; Q4 is reassigned to the companion morphic axis). The contribution is stated narrowly and honestly: the novelty is the axis. The consolidation and framing, not the individual threats, most of which are prior art. The work further distinguishes, explicitly, between categories that can be demonstrated as executable attacks in a simulator environment and those that cannot. Two categories: superposition manipulation (Q2) and a cross-framework convergence attack (Q3) are demonstrated as real, reproducible exploits against a live PennyLane/Qiskit cross-framework verification engine, with a benign control that correctly reads as defended. The remaining categories require a cryptographically-relevant quantum computer or physical quantum hardware and are explicitly out of scope for empirical demonstration; they are not claimed. Of the two demonstrated, the convergence attack (Q3) is the one genuinely quantum-specific and apparently-novel threat: it exists only because two quantum frameworks with opposite qubit-ordering conventions are cross-checked, allowing a real divergence to hide behind a benign convention gap. Keywords and subjects:threat modeling; moving-target defense; polymorphism; cyber deception; morphic security; adversarial robustness; STRIDE; LINDDUN; reproducible security research; post-quantum signatures; MASQUE; MASQUARAIDE QUANTA is one of two original axes in the MASQUE threat model within the MASQUARAIDE project, alongside the morphic-polymorphic axis CHIRAGE. This deposit includes the paper, the attack-demonstration harness, the cross-framework engine, and machine-readable results, released with an SHA3-256 file manifest and an ML-DSA-65 (FIPS 204) signature over the manifest anchor, so that every verdict can be reproduced or refuted.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21710552
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

QUANTA: A Quantum-Compute Threat Axis for Cross-Framework Verification Systems

Yen Amy
Zenodo (CERN European Organization for Nuclear Research)
Physical Unclonable Functions (PUFs) and Hardware Security
preprint

QUANTA: A Quantum-Compute Threat Axis for Cross-Framework Verification Systems

Yen Amy
preprint en

Abstract

Established threat-modeling frameworks contain no dedicated axis for quantum-compute threats. The individual threats are well studied, harvest-now-decrypt-later, Grover/Shor capability escalation, quantum side-channels, and circuit fingerprinting each have an active literature, but they are scattered across separate research communities and are not consolidated into a taxonomy usable within a standard data-flow threat-modeling process alongside STRIDE and LINDDUN. This work introduces QUANTA, a quantum-compute threat axis of seven categories (Q1 harvest-now-decrypt-later, Q2 superposition manipulation, Q3 cross-framework convergence attack, Q5 capability escalation, Q6 collapse side-channel, Q7 algorithm identification; Q4 is reassigned to the companion morphic axis). The contribution is stated narrowly and honestly: the novelty is the axis. The consolidation and framing, not the individual threats, most of which are prior art. The work further distinguishes, explicitly, between categories that can be demonstrated as executable attacks in a simulator environment and those that cannot. Two categories: superposition manipulation (Q2) and a cross-framework convergence attack (Q3) are demonstrated as real, reproducible exploits against a live PennyLane/Qiskit cross-framework verification engine, with a benign control that correctly reads as defended. The remaining categories require a cryptographically-relevant quantum computer or physical quantum hardware and are explicitly out of scope for empirical demonstration; they are not claimed. Of the two demonstrated, the convergence attack (Q3) is the one genuinely quantum-specific and apparently-novel threat: it exists only because two quantum frameworks with opposite qubit-ordering conventions are cross-checked, allowing a real divergence to hide behind a benign convention gap. Keywords and subjects:threat modeling; moving-target defense; polymorphism; cyber deception; morphic security; adversarial robustness; STRIDE; LINDDUN; reproducible security research; post-quantum signatures; MASQUE; MASQUARAIDE QUANTA is one of two original axes in the MASQUE threat model within the MASQUARAIDE project, alongside the morphic-polymorphic axis CHIRAGE. This deposit includes the paper, the attack-demonstration harness, the cross-framework engine, and machine-readable results, released with an SHA3-256 file manifest and an ML-DSA-65 (FIPS 204) signature over the manifest anchor, so that every verdict can be reproduced or refuted.

Zenodo (CERN European Organization for Nuclear Research)
University of Divinity (AU)
Peace, Justice and strong institutions
Physical Unclonable Functions (PUFs) and Hardware Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.