Hardware-based Mutation Strategies

Overview

Hardware-based mutation strategies are fuzzing techniques that use hardware-domain information to guide how test inputs are modified during hardware verification. In the available evidence, the term appears in the context of RTL fuzzing for CPU bug detection, where the INSTILLER fuzzer proposes “hardware-based seed selection and mutation strategies” to improve fuzzing performance.^[1]

Hardware-based mutation strategies are motivated by the fact that hardware bugs, such as CPU design bugs, must be detected before deployment, unlike many software bugs that can be patched after release.^[1]

Context: RTL Fuzzing

Register-transfer level (RTL) fuzzing tests hardware designs by generating and executing input instruction sequences against RTL implementations. The evidence identifies several challenges in prior CPU fuzzing work:

• RTL input instruction sequences can grow longer over time.^[1]
• Longer inputs may become ineffective for fuzzing.^[1]
• Prior work had difficulty realistically simulating interruptions during fuzzing.^[1]

INSTILLER, an RTL fuzzer based on ant colony optimization, addresses these issues by distilling input instructions, inserting interruptions and exceptions, and adding hardware-based seed selection and mutation strategies.^[1]

Role in INSTILLER

In INSTILLER, hardware-based mutation strategies are one component of a broader RTL fuzzing pipeline. The system includes:

1. Instruction distillation using a variant of ant colony optimization called VACO, intended to keep fuzzing inputs short and efficient.^[1]
2. Realistic interruption and exception insertion during input generation.^[1]
3. Hardware-based seed selection and mutation strategies to further improve fuzzing performance.^[1]

The evidence does not provide the internal mechanics of the hardware-based mutation strategies, but it explicitly identifies them as a performance-improving component of INSTILLER.^[1]

Technical Purpose

Within RTL fuzzing, mutation strategies are responsible for modifying existing inputs to explore new hardware states and behaviors. A hardware-based mutation strategy is therefore distinguished from a generic mutation strategy by being informed by hardware-specific considerations. In the INSTILLER context, such strategies are paired with hardware-based seed selection to improve the effectiveness of generated RTL instruction inputs.^[1]

Reported Effectiveness

INSTILLER was evaluated against state-of-the-art fuzzing work on real-world target CPU cores.^[1] The reported outcomes include:

These results are reported for the INSTILLER system as a whole; the evidence does not isolate the individual contribution of hardware-based mutation strategies from other components such as VACO-based instruction distillation or interruption/exception insertion.^[1]

Limitations of Available Evidence

The provided evidence establishes that hardware-based mutation strategies are part of INSTILLER and are intended to improve RTL fuzzing performance. However, it does not describe:

• The exact mutation operators used.
• Which hardware signals, structures, or coverage metrics guide mutation.
• How hardware-based mutation differs algorithmically from prior mutation strategies.
• The standalone performance impact of the mutation strategy independent of other INSTILLER components.

Therefore, any detailed implementation description would require consulting the full paper rather than relying only on the provided abstract-level evidence.

References

^[1]: Gen Zhang et al., “INSTILLER: Towards Efficient and Realistic RTL Fuzzing,” arXiv:2401.15967, DOI: 10.48550/arXiv.2401.15967.