Spectre Attacks: Exploiting Speculative Execution
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Abstract (arXiv)
Modern processors use branch prediction and speculative execution to maximize performance. For example, if the destination of a branch depends on a memory value that is in the process of being read, CPUs will try guess the destination and attempt to execute ahead. When the memory value finally arrives, the CPU either discards or commits the speculative computation. Speculative logic is unfaithful in how it executes, can access to the victim's memory and registers, and can perform operations with measurable side effects. Spectre attacks involve inducing a victim to speculatively perform operations that would not occur during correct program execution and which leak the victim's confidential information via a side channel to the adversary. This paper describes practical attacks that combine methodology from side channel attacks, fault attacks, and return-oriented programming that can read arbitrary memory from the victim's process. More broadly, the paper shows that speculative execution implementations violate the security assumptions underpinning numerous software security mechanisms, including operating system process separation, static analysis, containerization, just-in-time (JIT) compilation, and countermeasures to cache timing/side-channel attacks. These attacks represent a serious threat to actual systems, since vulnerable speculative execution capabilities are found in microprocessors from Intel, AMD, and ARM that are used in billions of devices. While makeshift processor-specific countermeasures are possible in some cases, sound solutions will require fixes to processor designs as well as updates to instruction set architectures (ISAs) to give hardware architects and software developers a common understanding as to what computation state CPU implementations are (and are not) permitted to leak.
Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Jan 2018.
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Citing papers per year: 2021: 5; 2022: 8; 2023: 3; 2024: 9; 2025: 11; 2026: 11.
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- 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
- 2024On the Societal Impact of Open Foundation Modelscited by 64
- 2024Unleashing the Power of Continual Learning on Non-Centralized Devices: A Surveycited by 23
- 2023No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device MLcited by 21
- 2025Auditing Prompt Caching in Language Model APIscited by 19
- 2024LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trustcited by 18
- 2025Selective KV-Cache Sharing to Mitigate Timing Side-Channels in LLM Inferencecited by 18
- 2022Secure Aggregation for Federated Learning in Flowercited by 15
- 2024Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interfacecited by 15
- 2021secureTF: A Secure TensorFlow Frameworkcited by 12
- 2025Dynamic Speculative Agent Planningcited by 10
- 2023HW-V2W-Map: Hardware Vulnerability to Weakness Mapping Framework for Root Cause Analysis with GPT-assisted Mitigation Suggestioncited by 8
35 more
- 2023ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patchingcited by 6
- 2024When Speculation Spills Secrets: Side Channels via Speculative Decoding In LLMscited by 6
- 2022Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniquescited by 5
- 2022Reward Delay Attacks on Deep Reinforcement Learningcited by 5
- 2021SHARKS: Smart Hacking Approaches for RisK Scanning in Internet-of-Things and Cyber-Physical Systems based on Machine Learningcited by 4
- 2025VET Your Agent: Towards Host-Independent Autonomy via Verifiable Execution Tracescited by 4
- 2022Edge Security: Challenges and Issuescited by 3
- 2024TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Modelscited by 3
- 2025Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challengescited by 3
- 2026Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Reviewcited by 3
- 2021Perun: Secure Multi-Stakeholder Machine Learning Framework with GPU Supportcited by 2
- 2025SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chipcited by 2
- 2025From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teamingcited by 2
- 2026AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agentscited by 2
- 2022A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automationcited by 1
- 2022Short Paper: Static and Microarchitectural ML-Based Approaches For Detecting Spectre Vulnerabilities and Attackscited by 1
- 2025Guillotine: Hypervisors for Isolating Malicious AIscited by 1
- 2025DR.FIX: Automatically Fixing Data Races at Industry Scalecited by 1
- 2026The Implications of Linguistic Illegibility for LLM Securitycited by 1
- 2021CloudShield: Real-time Anomaly Detection in the Cloudcited by 0
- 2022Comprehensive Efficiency Analysis of Machine Learning Algorithms for Developing Hardware-Based Cybersecurity Countermeasurescited by 0
- 2022MAD-EN: Microarchitectural Attack Detection through System-wide Energy Consumptioncited by 0
- 2024Props for Machine-Learning Securitycited by 0
- 2024Differentially Private Learned Indexescited by 0
- 2024VerifiableFL: Verifiable Claims for Federated Learning using Exclavescited by 0
- 2025Towards Reinforcement Learning for Exploration of Speculative Execution Vulnerabilitiescited by 0
- 2025Securing Private Federated Learning in a Malicious Setting: A Scalable TEE-Based Approach with Client Auditingcited by 0
- 2026Emerging Threats and Countermeasures in Neuromorphic Systems: A Surveycited by 0
- 2026Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environmentscited by 0
- 2026ATLAS: AI-Assisted Threat-to-Assertion Learning for System-on-Chip Security Verificationcited by 0
- 2026Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Modelscited by 0
- 2026uGen: An Agentic Framework for Generating Microarchitectural Attack PoCscited by 0
- 2026Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Toolscited by 0
- 2026HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzingcited by 0
- 2026Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timingcited by 0
- 2026The Implications of Linguistic Illegibility for LLM Security2 Sep 2026
- 2026Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing22 Jul 2026
- 2026HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzing7 Jul 2026
- 2026Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools1 Jun 2026
- 2026uGen: An Agentic Framework for Generating Microarchitectural Attack PoCs15 May 2026
- 2026AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agents27 Apr 2026
- 2026Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models26 Mar 2026
- 2026Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review19 Mar 2026
- 2026ATLAS: AI-Assisted Threat-to-Assertion Learning for System-on-Chip Security Verification1 Mar 2026
- 2026Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environments23 Feb 2026
- 2026Emerging Threats and Countermeasures in Neuromorphic Systems: A Survey23 Jan 2026
- 2025VET Your Agent: Towards Host-Independent Autonomy via Verifiable Execution Traces17 Dec 2025
35 more
- 2025From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming14 Sep 2025
- 2025Securing Private Federated Learning in a Malicious Setting: A Scalable TEE-Based Approach with Client Auditing10 Sep 2025
- 2025Dynamic Speculative Agent Planning2 Sep 2025
- 2025SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip18 Aug 2025
- 2025Selective KV-Cache Sharing to Mitigate Timing Side-Channels in LLM Inference11 Aug 2025
- 2025Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challenges30 May 2025
- 2025DR.FIX: Automatically Fixing Data Races at Industry Scale22 Apr 2025
- 2025Guillotine: Hypervisors for Isolating Malicious AIs22 Apr 2025
- 2025Towards Reinforcement Learning for Exploration of Speculative Execution Vulnerabilities24 Feb 2025
- 2025Auditing Prompt Caching in Language Model APIs11 Feb 2025
- 2024Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey18 Dec 2024
- 2024VerifiableFL: Verifiable Claims for Federated Learning using Exclaves13 Dec 2024
- 2024TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models15 Nov 2024
- 2024When Speculation Spills Secrets: Side Channels via Speculative Decoding In LLMs1 Nov 2024
- 2024Differentially Private Learned Indexes28 Oct 2024
- 2024Props for Machine-Learning Security27 Oct 2024
- 2024Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface30 Sep 2024
- 2024LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust11 May 2024
- 2024On the Societal Impact of Open Foundation Models27 Feb 2024
- 2023HW-V2W-Map: Hardware Vulnerability to Weakness Mapping Framework for Root Cause Analysis with GPT-assisted Mitigation Suggestion21 Dec 2023
- 2023No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML11 Oct 2023
- 2023ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching24 Aug 2023
- 2022Short Paper: Static and Microarchitectural ML-Based Approaches For Detecting Spectre Vulnerabilities and Attacks26 Oct 2022
- 2022Reward Delay Attacks on Deep Reinforcement Learning8 Sep 2022
- 2022Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniques18 Jul 2022
- 2022Edge Security: Challenges and Issues14 Jun 2022
- 2022MAD-EN: Microarchitectural Attack Detection through System-wide Energy Consumption31 May 2022
- 2022Secure Aggregation for Federated Learning in Flower12 May 2022
- 2022A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation19 Apr 2022
- 2022Comprehensive Efficiency Analysis of Machine Learning Algorithms for Developing Hardware-Based Cybersecurity Countermeasures5 Jan 2022
- 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detection4 Nov 2021
- 2021CloudShield: Real-time Anomaly Detection in the Cloud20 Aug 2021
- 2021Perun: Secure Multi-Stakeholder Machine Learning Framework with GPU Support31 Mar 2021
- 2021secureTF: A Secure TensorFlow Framework20 Jan 2021
- 2021SHARKS: Smart Hacking Approaches for RisK Scanning in Internet-of-Things and Cyber-Physical Systems based on Machine Learning7 Jan 2021
- 2024Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interfacecited by 15
- 2025Dynamic Speculative Agent Planningcited by 10
- 2025VET Your Agent: Towards Host-Independent Autonomy via Verifiable Execution Tracescited by 4
- 2026AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agentscited by 2
- 2026uGen: An Agentic Framework for Generating Microarchitectural Attack PoCscited by 0
- 2026Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Toolscited by 0
- 2026Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools1 Jun 2026
- 2026uGen: An Agentic Framework for Generating Microarchitectural Attack PoCs15 May 2026
- 2026AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agents27 Apr 2026
- 2025VET Your Agent: Towards Host-Independent Autonomy via Verifiable Execution Traces17 Dec 2025
- 2025Dynamic Speculative Agent Planning2 Sep 2025
- 2024Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface30 Sep 2024
- 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
- 2024On the Societal Impact of Open Foundation Modelscited by 64
- 2024Unleashing the Power of Continual Learning on Non-Centralized Devices: A Surveycited by 23
- 2023No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device MLcited by 21
- 2025Auditing Prompt Caching in Language Model APIscited by 19
- 2024LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trustcited by 18
- 2022Secure Aggregation for Federated Learning in Flowercited by 15
- 2021secureTF: A Secure TensorFlow Frameworkcited by 12
- 2023HW-V2W-Map: Hardware Vulnerability to Weakness Mapping Framework for Root Cause Analysis with GPT-assisted Mitigation Suggestioncited by 8
- 2023ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patchingcited by 6
- 2022Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniquescited by 5
- 2022Reward Delay Attacks on Deep Reinforcement Learningcited by 5
12 most cited of 36 All 36 (JSON)
- 2026The Implications of Linguistic Illegibility for LLM Security2 Sep 2026
- 2026HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzing7 Jul 2026
- 2026Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review19 Mar 2026
- 2026ATLAS: AI-Assisted Threat-to-Assertion Learning for System-on-Chip Security Verification1 Mar 2026
- 2026Emerging Threats and Countermeasures in Neuromorphic Systems: A Survey23 Jan 2026
- 2025From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming14 Sep 2025
- 2025Securing Private Federated Learning in a Malicious Setting: A Scalable TEE-Based Approach with Client Auditing10 Sep 2025
- 2025SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip18 Aug 2025
- 2025Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challenges30 May 2025
- 2025DR.FIX: Automatically Fixing Data Races at Industry Scale22 Apr 2025
- 2025Guillotine: Hypervisors for Isolating Malicious AIs22 Apr 2025
- 2025Towards Reinforcement Learning for Exploration of Speculative Execution Vulnerabilities24 Feb 2025
12 newest of 36 All 36 (JSON)