Christof Torres

Christof Ferreira Torres

Ph.D. Candidate at the University of Luxembourg

About Me

I am currently a doctoral researcher at the University of Luxembourg. I am under the supervision of Dr. Radu State (University of Luxembourg) and Dr. Arthur Gervais (Imperial College London).

Prior to that, I have worked as an associate researcher at the Fraunhofer Institute for Applied and Integrated Security (AISEC) in Munich, Germany.

Selected Publications

  • Frontrunner Jones and the Raiders of the Dark Forest: An Empirical Study of Frontrunning on the Ethereum Blockchain

    Christof Ferreira Torres, Ramiro Camino, Radu State

    Ethereum prospered the inception of a plethora of smart contract applications, ranging from gambling games to decentralized finance. However, Ethereum is also considered a highly adversarial environment, where vulnerable smart contracts will eventually be exploited. Recently, Ethereum's pool of pending transaction has become a far more aggressive environment. In the hope of making some profit, attackers continuously monitor the transaction pool and try to front-run their victims' transactions by either displacing or suppressing them, or strategically inserting their transactions. This paper aims to shed some light into what is known as a dark forest and uncover these predators' actions. We present a methodology to efficiently measure the three types of frontrunning: displacement, insertion, and suppression. We perform a large-scale analysis on more than 11M blocks and identify almost 200K attacks with an accumulated profit of 18.41M USD for the attackers, providing evidence that frontrunning is both, lucrative and a prevalent issue.

  • ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts

    Christof Ferreira Torres, Antonio Ken Iannillo, Arthur Gervais, Radu State
    6th IEEE European Symposium on Security and Privacy, Vienna, Austria, October 7–22, 2021 (EuroS&P 2021)

    Smart contracts are Turing-complete programs executed across the blockchain. Unlike traditional programs, once deployed, they cannot be modified. As smart contracts carry more value, they become an exciting target for attackers. Over the last years, they suffered from exploits costing millions of dollars due to simple programming mistakes. As a result, a variety of tools for detecting bugs have been proposed. Most of these tools rely on symbolic execution, which yields many false positives due to over-approximation. Recently, many fuzzers have been proposed to detect bugs in smart contracts. However, these tend to be more effective in finding shallow bugs and less effective in finding bugs that lie deep in the execution, therefore achieving low code coverage and many false negatives. An alternative that has proven to achieve good results in traditional programs is hybrid fuzzing, a combination of symbolic execution and fuzzing. In this work, we study hybrid fuzzing on smart contracts and present ConFuzzius, the first hybrid fuzzer for smart contracts. ConFuzzius uses evolutionary fuzzing to exercise shallow parts of a smart contract and constraint solving to generate inputs that satisfy complex conditions that prevent evolutionary fuzzing from exploring deeper parts. Moreover, ConFuzzius leverages dynamic data dependency analysis to efficiently generate sequences of transactions that are more likely to result in contract states in which bugs may be hidden. We evaluate the effectiveness of ConFuzzius by comparing it with state-of-the-art symbolic execution tools and fuzzers for smart contracts. Our evaluation on a curated dataset of 128 contracts and a dataset of 21K real-world contracts shows that our hybrid approach detects more bugs than state-of-the-art tools (up to 23%) and that it outperforms existing tools in terms of code coverage (up to 69%). We also demonstrate that data dependency analysis can boost bug detection up to 18%.

  • The Eye of Horus: Spotting and Analyzing Attacks on Ethereum Smart Contracts

    Christof Ferreira Torres, Antonio Ken Iannillo, Arthur Gervais, Radu State
    25th International Conference on Financial Cryptography and Data Security, Grenda, March 1–5, 2021 (FC 2021)

    In recent years, Ethereum gained tremendously in popularity, growing from a daily transaction average of 10K in January 2016 to an average of 500K in January 2020. Similarly, smart contracts began to carry more value, making them appealing targets for attackers. As a result, they started to become victims of attacks, costing millions of dollars. In response to these attacks, both academia and industry proposed a plethora of tools to scan smart contracts for vulnerabilities before deploying them on the blockchain. However, most of these tools solely focus on detecting vulnerabilities and not attacks, let alone quantifying or tracing the number of stolen assets. In this paper, we present Horus, a framework that empowers the automated detection and investigation of smart contract attacks based on logic-driven and graph-driven analysis of transactions. Horus provides quick means to quantify and trace the flow of stolen assets across the Ethereum blockchain. We perform a large-scale analysis of all the smart contracts deployed on Ethereum until May 2020. We identified 1,888 attacked smart contracts and 8,095 adversarial transactions in the wild. Our investigation shows that the number of attacks did not necessarily decrease over the past few years, but for some vulnerabilities remained constant. Finally, we also demonstrate the practicality of our framework via an in-depth analysis on the recent Uniswap and attacks.

  • High-Frequency Trading on Decentralized On-Chain Exchanges

    Liyi Zhou, Kaihua Qin, Christof Ferreira Torres, Duc V Le, Arthur Gervais
    42nd IEEE Symposium onSecurity and Privacy, May 23-27, 2021 (S&P 2021)

    Decentralized exchanges (DEXs) allow parties to participate in financial markets while retaining full custody of their funds. However, the transparency of blockchain-based DEX in combination with the latency for transactions to be processed, makes market-manipulation feasible. For instance, adversaries could perform front-running -- the practice of exploiting (typically non-public) information that may change the price of an asset for financial gain. In this work we formalize, analytically exposit and empirically evaluate an augmented variant of front-running: sandwich attacks, which involve front- and back-running victim transactions on a blockchain-based DEX. We quantify the probability of an adversarial trader being able to undertake the attack, based on the relative positioning of a transaction within a blockchain block. We find that a single adversarial trader can earn a daily revenue of over several thousand USD when performing sandwich attacks on one particular DEX -- Uniswap, an exchange with over 5M USD daily trading volume by June 2020. In addition to a single-adversary game, we simulate the outcome of sandwich attacks under multiple competing adversaries, to account for the real-world trading environment.

  • ÆGIS: Shielding Vulnerable Smart Contracts Against Attacks

    Christof Ferreira Torres, Mathis Baden, Robert Norvill, Beltran Fiz Pontiveros, Hugo Jonker, Sjouke Mauw
    15th ACM Asia Conference on Computer and Communications Security, Taipei, Taiwan, October 5–9, 2020 (AsiaCCS 2020)

    In recent years, smart contracts have suffered major exploits, costing millions of dollars. Unlike traditional programs, smart contracts are deployed on a blockchain. As such, they cannot be modified once deployed. Though various tools have been proposed to detect vulnerable smart contracts, the majority fails to protect vulnerable contracts that have already been deployed on the blockchain. Only very few solutions have been proposed so far to tackle the issue of post-deployment. However, these solutions suffer from low precision and are not generic enough to prevent any type of attack. In this work, we introduce ÆGIS, a dynamic analysis tool that protects smart contracts from being exploited during runtime. Its capability of detecting new vulnerabilities can easily be extended through so-called attack patterns. These patterns are written in a domain-specific language that is tailored to the execution model of Ethereum smart contracts. The language enables the description of malicious control and data flows. In addition, we propose a novel mechanism to streamline and speed up the process of managing attack patterns. Patterns are voted upon and stored via a smart contract, thus leveraging the benefits of tamper-resistance and transparency provided by the blockchain. We compare ÆGIS to current state-of-the-art tools and demonstrate that our solution achieves higher precision in detecting attacks. Finally, we performa large-scale analysis on the first 4.5 million blocks of the Ethereum blockchain, thereby confirming the occurrences of well reported and yet unreported attacks in the wild.

  • ÆGIS: Smart Shielding of Smart Contracts

    Christof Ferreira Torres, Mathis Baden, Robert Norvill, Hugo Jonker
    26th ACM Conference on Computer and Communications Security, London, UK, November 11-15, 2019 (CCS 2019)

    In recent years, smart contracts have suffered major exploits, losing millions of dollars. Unlike traditional programs, smart contracts cannot be updated once deployed. Though various tools were proposed to detect vulnerable smart contracts, they all fail to protect contracts that have already been deployed on the blockchain. Moreover, they focus on vulnerabilities, but do not address scams (e.g., honeypots). In this work, we introduce ÆGIS, a tool that shields smart contracts and users on the blockchain from being exploited. To this end, ÆGIS reverts transactions in real-time based on pattern matching. These patterns encode the detection of malicious transactions that trigger exploits or scams. New patterns are voted upon and stored via a smart contract, thus leveraging the benefits of tamper-resistance and transparency provided by blockchain. By allowing its protection to be updated, the smart contract acts as a smart shield.

  • The Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts

    Christof Ferreira Torres, Mathis Steichen, Radu State
    28th USENIX Security Symposium, USENIX Security 2019, Santa Clara, CA, USA, August 14-16, 2019. (USENIX Security 2019)
    Paper Slides PoC

    Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts – programs that are executed across a decentralised network of nodes. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise, where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying seemingly vulnerable contracts that contain hidden traps. This new type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypot smart contracts, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HoneyBadger – a tool that employs symbolic execution and well defined heuristics to expose honeypots. We perform a large-scale analysis on more than 2 million smart contracts and show that our tool not only achieves high precision, but is also highly efficient. We identify 690 honeypot smart contracts as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots.

  • Osiris: Hunting for Integer Bugs in Ethereum Smart Contracts

    Christof Ferreira Torres, Julian Schütte, Radu State
    34th Annual Computer Security Applications Conference, ACSAC 2018, San Juan, PR, USA, December 3-7, 2018. (ACSAC 2018)
    Paper PoC

    The capability of executing so-called smart contracts in a decentralised manner is one of the compelling features of modern blockchains. Smart contracts are fully fledged programs which cannot be changed once deployed to the blockchain. They typically implement the business logic of distributed apps and carry billions of dollars worth of coins. In that respect, it is imperative that smart contracts are correct and have no vulnerabilities or bugs. However, research has identified different classes of vulnerabilities in smart contracts, some of which led to prominent multi-million dollar fraud cases. In this paper we focus on vulnerabilities related to integer bugs, a class of bugs that is particularly difficult to avoid due to some characteristics of the Ethereum Virtual Machine and the Solidity programming language. In this paper, we introduce Osiris – a framework that combines symbolic execution and taint analysis, in order to accurately find integer bugs in Ethereum smart contracts. Osiris detects a greater range of bugs than existing tools, while providing a better specificity of its detection. We have evaluated its performance on a large experimental dataset containing more than 1.2 million smart contracts. We found that 42,108 contracts contain integer bugs. Besides being able to identify several vulnerabilities that have been reported in the past few months, we were also able to identify a yet unknown critical vulnerability in a couple of smart contracts that are currently deployed on the Ethereum blockchain.

  • Investigating Fingerprinters and Fingerprinting-Alike Behaviour of Android Applications

    Christof Ferreira Torres, Hugo Jonker
    23rd European Symposium on Research in Computer Security, ESORICS 2018, Barcelona, Spain, September 3-7, 2018. (ESORICS 2018)

    Fingerprinting of browsers has been thoroughly investigated. In contrast, mobile phone applications offer a far wider array of attributes for profiling, yet fingerprinting practices on this platform have hardly received attention. In this paper, we present the first (to our knowledge) investigation of Android libraries by commercial fingerprinters. Interestingly enough, there is a marked difference with fingerprinting desktop browsers. We did not find evidence of typical fingerprinting techniques such as canvas fingerprinting. Secondly, we searched for behaviour resembling that of commercial fingerprinters. We performed a detailed analysis of six similar libraries. Thirdly, we investigated ~30,000 apps and found that roughly 19% of these apps is using one of these libraries. Finally, we checked how often these libraries were used by apps subject to the Children’s Online Privacy Protection Act (i.e. apps targeted explicitly at children), and found that these libraries were included 21 times.

  • FP-Block: Usable Web Privacy by Controlling Browser Fingerprinting

    Christof Ferreira Torres, Hugo Jonker, Sjouke Mauw
    20th European Symposium on Research in Computer Security, Vienna, Austria, September 21-25, 2015. (ESORICS 2015)
    Paper Slides PoC

    Online tracking of users is used for benign goals, such as detecting fraudulent logins, but also to invade user privacy. We posit that for non-oppressed users, tracking within one website does not have a substantial negative impact on privacy, while it enables legitimate benefits. In contrast, cross-domain tracking negatively impacts user privacy, while being of little benefit to the user. Existing methods to counter fingerprint-based tracking treat cross-domain tracking and regular tracking the same. This often results in hampering or disabling desired functionality, such as embedded videos. By distinguishing between regular and cross-domain tracking, more desired functionality can be preserved. We have developed a prototype tool, FP-Block, that counters cross-domain fingerprint-based tracking while still allowing regular tracking. FP-Block ensures that any embedded party will see a different, unrelatable fingerprint for each site on which it is embedded. Thus, the user’s fingerprint can no longer be tracked across the web, while desired functionality is better preserved compared to existing methods.

Research Interests

  • Security and Privacy of Distributed Ledgers
  • Browser and Mobile Fingerprinting