Lucas Davi

Tobias Cloosters, Pascal Winkler, Jens-Rene Giesen et al.

Solana is rapidly gaining traction among smart contract developers and users. However, its growing adoption has been accompanied by a series of major security incidents, which have spurred research into automated analysis techniques for Solana smart contracts. Unfortunately, existing approaches do not address the unique and complex account model of Solana. In this paper, we propose SseRex, the first symbolic execution vulnerability detection approach for finding Solana-specific bugs such as missing owner checks, missing signer checks, and missing key checks, as well as arbitrary cross-program invocations. Our evaluation of 8,714 bytecode-only contracts shows that our approach outperforms existing approaches and identifies potential bugs in 467 different contracts. Additionally, we analyzed 120 open-source Solana projects and conducted in-depth case studies on four of them. Our findings reveal that subtle, easily overlooked issues often serve as the root cause of severe exploits, further highlighting the need for specialized analysis tools like SseRex.

Martin Herrmann, Oussama Draissi, Christian Niesler et al.

Microarchitectural vulnerabilities increasingly undermine the assumption that hardware can be treated as a reliable root of trust. Prevention mechanisms often lag behind evolving attack techniques, leaving deployed systems unable to assume continued trustworthiness. We propose a shift from prevention to detection through microarchitectural-aware remote attestation. As a first instantiation of this idea, we present HammerWatch, a Rowhammer-aware remote attestation protocol that enables an external verifier to assess whether a system exhibits hardware-induced disturbance behavior. HammerWatch leverages memory-level evidence available on commodity platforms, specifically Machine-Check Exceptions (MCEs) from ECC DRAM and counter-based indicators from Per-Row Activation Counting (PRAC), and protects these measurements against kernel-level adversaries using TPM-anchored hash chains. We implement HammerWatch on commodity hardware and evaluate it on 20000 simulated benign and malicious access patterns. Our results show that the verifier reliably distinguishes Rowhammer-like behavior from benign operation under conservative heuristics, demonstrating that detection-oriented attestation is feasible and can complement incomplete prevention mechanisms

Oussama Draissi, Mark Günzel, Ahmad-Reza Sadeghi et al.

WebAssembly's (Wasm) monolithic linear memory model facilitates memory corruption attacks that can escalate to cross-site scripting in browsers or go undetected when a malicious host tampers with a module's state. Existing defenses rely on invasive binary instrumentation or custom runtimes, and do not address runtime integrity verification under an adversarial host model. We present Walma, a framework for WebAssembly Linear Memory Attestation that leverages machine learning to detect memory corruption and external tampering by classifying memory snapshots. We evaluate Walma on six real-world CVE-affected applications across three verification backends (cpu-wasm, cpu-tch, gpu) and three instrumentation policies. Our results demonstrate that CNN-based classification can effectively detect memory corruption in applications with structured memory layouts, with coarse-grained boundary checks incurring as low as 1.07x overhead, while fine-grained monitoring introduces higher (1.5x--1.8x) but predictable costs. Our evaluation quantifies the accuracy and overhead trade-offs across deployment configurations, demonstrating the practical feasibility of ML-based memory attestation for WebAssembly.

David Paaßen, Sebastian Surminski, Michael Rodler et al.

Fuzzing has become one of the most popular techniques to identify bugs in software. To improve the fuzzing process, a plethora of techniques have recently appeared in academic literature. However, evaluating and comparing these techniques is challenging as fuzzers depend on randomness when generating test inputs. Commonly, existing evaluations only partially follow best practices for fuzzing evaluations. We argue that the reason for this are twofold. First, it is unclear if the proposed guidelines are necessary due to the lack of comprehensive empirical data in the case of fuzz testing. Second, there does not yet exist a framework that integrates statistical evaluation techniques to enable fair comparison of fuzzers. To address these limitations, we introduce a novel fuzzing evaluation framework called SENF (Statistical EvaluatioN of Fuzzers). We demonstrate the practical applicability of our framework by utilizing the most wide-spread fuzzer AFL as our baseline fuzzer and exploring the impact of different evaluation parameters (e.g., the number of repetitions or run-time), compilers, seeds, and fuzzing strategies. Using our evaluation framework, we show that supposedly small changes of the parameters can have a major influence on the measured performance of a fuzzer.

Jan Philipp Thoma, Christian Niesler, Dominic Funke et al.

In the recent past, we have witnessed the shift towards attacks on the microarchitectural CPU level. In particular, cache side-channels play a predominant role as they allow an attacker to exfiltrate secret information by exploiting the CPU microarchitecture. These subtle attacks exploit the architectural visibility of conflicting cache addresses. In this paper, we present ClepsydraCache, which mitigates state-of-the-art cache attacks using a novel combination of cache decay and index randomization. Each cache entry is linked with a Time-To-Live (TTL) value. We propose a new dynamic scheduling mechanism of the TTL which plays a fundamental role in preventing those attacks while maintaining performance. ClepsydraCache efficiently protects against the latest cache attacks such as Prime+(Prune+)Probe. We present a full prototype in gem5 and lay out a proof-of-concept hardware design of the TTL mechanism, which demonstrates the feasibility of deploying ClepsydraCache in real-world systems.

Michael Rodler, Wenting Li, Ghassan O. Karame et al.

Recent attacks exploiting errors in smart contract code had devastating consequences thereby questioning the benefits of this technology. It is currently highly challenging to fix errors and deploy a patched contract in time. Instant patching is especially important since smart contracts are always online due to the distributed nature of blockchain systems. They also manage considerable amounts of assets, which are at risk and often beyond recovery after an attack. Existing solutions to upgrade smart contracts depend on manual and error-prone processes. This paper presents a framework, called EVMPatch, to instantly and automatically patch faulty smart contracts. EVMPatch features a bytecode rewriting engine for the popular Ethereum blockchain, and transparently/automatically rewrites common off-the-shelf contracts to upgradable contracts. The proof-of-concept implementation of EVMPatch automatically hardens smart contracts that are vulnerable to integer over/underflows and access control errors, but can be easily extended to cover more bug classes. Our extensive evaluation on 14,000 real-world (vulnerable) contracts demonstrate that our approach successfully blocks attack transactions launched on these contracts, while keeping the intended functionality of the contract intact. We perform a study with experienced software developers, showing that EVMPatch is practical, and reduces the time for converting a given Solidity smart contract to an upgradable contract by 97.6 %, while ensuring functional equivalence to the original contract.

Tobias Cloosters, Michael Rodler, Lucas Davi

Intel's Software Guard Extensions (SGX) introduced new instructions to switch the processor to enclave mode which protects it from introspection. While the enclave mode strongly protects the memory and the state of the processor, it cannot withstand memory corruption errors inside the enclave code. In this paper, we show that the attack surface of SGX enclaves provides new challenges for enclave developers as exploitable memory corruption vulnerabilities are easily introduced into enclave code. We develop TeeRex to automatically analyze enclave binary code for vulnerabilities introduced at the host-to-enclave boundary by means of symbolic execution. Our evaluation on public enclave binaries reveal that many of them suffer from memory corruption errors allowing an attacker to corrupt function pointers or perform arbitrary memory writes. As we will show, TeeRex features a specifically tailored framework for SGX enclaves that allows simple proof-of-concept exploit construction to assess the discovered vulnerabilities. Our findings reveal vulnerabilities in multiple enclaves, including enclaves developed by Intel, Baidu, and WolfSSL, as well as biometric fingerprint software deployed on popular laptop brands.

Jannik Pewny, Philipp Koppe, Lucas Davi et al.

Just-in-time return-oriented programming (JIT-ROP) is a powerful memory corruption attack that bypasses various forms of code randomization. Execute-only memory (XOM) can potentially prevent these attacks, but requires source code. In contrast, destructive code reads (DCR) provide a trade-off between security and legacy compatibility. The common belief is that DCR provides strong protection if combined with a high-entropy code randomization. The contribution of this paper is twofold: first, we demonstrate that DCR can be bypassed regardless of the underlying code randomization scheme. To this end, we show novel, generic attacks that infer the code layout for highly randomized program code. Second, we present the design and implementation of BGDX (Byte-Granular DCR and XOM), a novel mitigation technique that protects legacy binaries against code inference attacks. BGDX enforces memory permissions on a byte-granular level allowing us to combine DCR and XOM for legacy, off-the-shelf binaries. Our evaluation shows that BGDX is not only effective, but highly efficient, imposing only a geometric mean performance overhead of 3.95% on SPEC.

Sridhar Adepu, Ferdinand Brasser, Luis Garcia et al.

Cyber-physical control systems, such as industrial control systems (ICS), are increasingly targeted by cyberattacks. Such attacks can potentially cause tremendous damage, affect critical infrastructure or even jeopardize human life when the system does not behave as intended. Cyberattacks, however, are not new and decades of security research have developed plenty of solutions to thwart them. Unfortunately, many of these solutions cannot be easily applied to safety-critical cyber-physical systems. Further, the attack surface of ICS is quite different from what can be commonly assumed in classical IT systems. We present Scadman, a system with the goal to preserve the Control Behavior Integrity (CBI) of distributed cyber-physical systems. By observing the system-wide behavior, the correctness of individual controllers in the system can be verified. This allows Scadman to detect a wide range of attacks against controllers, like programmable logic controller (PLCs), including malware attacks, code-reuse and data-only attacks. We implemented and evaluated Scadman based on a real-world water treatment testbed for research and training on ICS security. Our results show that we can detect a wide range of attacks--including attacks that have previously been undetectable by typical state estimation techniques--while causing no false-positive warning for nominal threshold values.

Michael Rodler, Wenting Li, Ghassan O. Karame et al.

Recently, a number of existing blockchain systems have witnessed major bugs and vulnerabilities within smart contracts. Although the literature features a number of proposals for securing smart contracts, these proposals mostly focus on proving the correctness or absence of a certain type of vulnerability within a contract, but cannot protect deployed (legacy) contracts from being exploited. In this paper, we address this problem in the context of re-entrancy exploits and propose a novel smart contract security technology, dubbed Sereum (Secure Ethereum), which protects existing, deployed contracts against re-entrancy attacks in a backwards compatible way based on run-time monitoring and validation. Sereum does neither require any modification nor any semantic knowledge of existing contracts. By means of implementation and evaluation using the Ethereum blockchain, we show that Sereum covers the actual execution flow of a smart contract to accurately detect and prevent attacks with a false positive rate as small as 0.06% and with negligible run-time overhead. As a by-product, we develop three advanced re-entrancy attacks to demonstrate the limitations of existing offline vulnerability analysis tools.

Thomas Nyman, Jan-Erik Ekberg, Lucas Davi et al.

With the increasing scale of deployment of Internet of Things (IoT), concerns about IoT security have become more urgent. In particular, memory corruption attacks play a predominant role as they allow remote compromise of IoT devices. Control-flow integrity (CFI) is a promising and generic defense technique against these attacks. However, given the nature of IoT deployments, existing protection mechanisms for traditional computing environments (including CFI) need to be adapted to the IoT setting. In this paper, we describe the challenges of enabling CFI on microcontroller (MCU) based IoT devices. We then present CaRE, the first interrupt-aware CFI scheme for low-end MCUs. CaRE uses a novel way of protecting the CFI metadata by leveraging TrustZone-M security extensions introduced in the ARMv8-M architecture. Its binary instrumentation approach preserves the memory layout of the target MCU software, allowing pre-built bare-metal binary code to be protected by CaRE. We describe our implementation on a Cortex-M Prototyping System and demonstrate that CaRE is secure while imposing acceptable performance and memory impact.

Ghada Dessouky, Shaza Zeitouni, Thomas Nyman et al.

Attacks targeting software on embedded systems are becoming increasingly prevalent. Remote attestation is a mechanism that allows establishing trust in embedded devices. However, existing attestation schemes are either static and cannot detect control-flow attacks, or require instrumentation of software incurring high performance overheads. To overcome these limitations, we present LO-FAT, the first practical hardware-based approach to control-flow attestation. By leveraging existing processor hardware features and commonly-used IP blocks, our approach enables efficient control-flow attestation without requiring software instrumentation. We show that our proof-of-concept implementation based on a RISC-V SoC incurs no processor stalls and requires reasonable area overhead.

Dean Sullivan, Orlando Arias, David Gens et al.

Instruction set randomization (ISR) was initially proposed with the main goal of countering code-injection attacks. However, ISR seems to have lost its appeal since code-injection attacks became less attractive because protection mechanisms such as data execution prevention (DEP) as well as code-reuse attacks became more prevalent. In this paper, we show that ISR can be extended to also protect against code-reuse attacks while at the same time offering security guarantees similar to those of software diversity, control-flow integrity, and information hiding. We present Scylla, a scheme that deploys a new technique for in-place code encryption to hide the code layout of a randomized binary, and restricts the control flow to a benign execution path. This allows us to i) implicitly restrict control-flow targets to basic block entries without requiring the extraction of a control-flow graph, ii) achieve execution integrity within legitimate basic blocks, and iii) hide the underlying code layout under malicious read access to the program. Our analysis demonstrates that Scylla is capable of preventing state-of-the-art attacks such as just-in-time return-oriented programming (JIT-ROP) and crash-resistant oriented programming (CROP). We extensively evaluate our prototype implementation of Scylla and show feasible performance overhead. We also provide details on how this overhead can be significantly reduced with dedicated hardware support.

Ferdinand Brasser, Lucas Davi, David Gens et al.

Rowhammer is a hardware bug that can be exploited to implement privilege escalation and remote code execution attacks. Previous proposals on rowhammer mitigation either require hardware changes or follow heuristic-based approaches (based on CPU performance counters). To date, there exists no instant protection against rowhammer attacks on legacy systems. In this paper, we present the design and implementation of two practical and efficient software-only defenses against rowhammer attacks. Our defenses prevent the attacker from leveraging rowhammer to corrupt physically co-located data in memory that is owned by a different system entity. Our first defense, B-CATT, extends the system bootloader to disable vulnerable physical memory. B-CATT is highly practical, does not require changes to the operating system, and can be deployed on virtually all x86-based systems. While B-CATT is able to stop all known rowhammer attacks, it does not yet tackle the fundamental problem of missing memory isolation in physical memory. To address this problem, we introduce our second defense G-CATT, a generic solution that extends the physical memory allocator of the OS to physically isolate the memory of different system entities (e.g., kernel and user space). As proof of concept, we implemented B-CATT on x86, and our generic defense, G-CATT, on x86 and ARM to mitigate rowhammer-based kernel exploits. Our extensive evaluation shows that both mitigation schemes (i) can stop available real- world rowhammer attacks, (ii) impose virtually no run-time overhead for common user and kernel benchmarks as well as commonly used applications, and (iii) do not affect the stability of the overall system.

Răzvan Deaconescu, Luke Deshotels, Mihai Bucicoiu et al.

In order to limit the damage of malware on Mac OS X and iOS, Apple uses sandboxing, a kernel-level security layer that provides tight constraints for system calls. Particularly used for Apple iOS, sandboxing prevents apps from executing potentially dangerous actions, by defining rules in a sandbox profile. Investigating Apple's built-in sandbox profiles is difficult as they are compiled and stored in binary format. We present SandBlaster, a software bundle that is able to reverse/decompile Apple binary sandbox profiles to their original human readable SBPL (SandBox Profile Language) format. We use SandBlaster to reverse all built-in Apple iOS binary sandbox profiles for iOS 7, 8 and 9. Our tool is, to the best of our knowledge, the first to provide a full reversing of the Apple sandbox, shedding light into the inner workings of Apple sandbox profiles and providing essential support for security researchers and professionals interested in Apple security mechanisms.

Tigist Abera, N. Asokan, Lucas Davi et al.

Remote attestation is a crucial security service particularly relevant to increasingly popular IoT (and other embedded) devices. It allows a trusted party (verifier) to learn the state of a remote, and potentially malware-infected, device (prover). Most existing approaches are static in nature and only check whether benign software is initially loaded on the prover. However, they are vulnerable to run-time attacks that hijack the application's control or data flow, e.g., via return-oriented programming or data-oriented exploits. As a concrete step towards more comprehensive run-time remote attestation, we present the design and implementation of Control- FLow ATtestation (C-FLAT) that enables remote attestation of an application's control-flow path, without requiring the source code. We describe a full prototype implementation of C-FLAT on Raspberry Pi using its ARM TrustZone hardware security extensions. We evaluate C-FLAT's performance using a real-world embedded (cyber-physical) application, and demonstrate its efficacy against control-flow hijacking attacks.