An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols

Coercion resistance is an important and one of the most intricate security requirements of electronic voting protocols. Several definitions of coercion resistance have been proposed in the literature, including definitions based on symbolic models. However, existing definitions in such models are rather restricted in their scope and quite complex. In this paper, we therefore propose a new definition of coercion resistance in a symbolic setting, based on an epistemic approach. Our definition is relatively simple and intuitive. It allows for a fine-grained formulation of coercion resistance and can be stated independently of a specific, symbolic protocol and adversary model. As a proof of concept, we apply our definition to three voting protocols. In particular, we carry out the first rigorous analysis of the recently proposed Civitas system. We precisely identify those conditions under which this system guarantees coercion resistance or fails to be coercion resistant. We also analyze protocols proposed by Lee et al. and Okamoto.Comment: An extended version of a paper from IEEE Symposium on Security and Privacy (S&P) 200

SSPFA: Effective Stack Smashing Protection for Android OS

[EN] In this paper, we detail why the stack smashing protector (SSP), one of the most effective techniques to mitigate stack bufferoverflow attacks, fails to protect the Android operating system and thus causes a false sense of security that affects all Androiddevices. We detail weaknesses of existing SSP implementations, revealing that current SSP is not secure. We propose SSPFA,the first effective and practical SSP for Android devices. SSPFA provides security against stack buffer overflows withoutchanging the underlying architecture. SSPFA has been implemented and tested on several real devices showing that it is notintrusive, and it is binary-compatible with Android applications. Extensive empirical validation has been carried out over theproposed solution.This work was partially funded by Universitat Politecnica de Valencia (Grant No. 20160251-ASLR-NG).Marco Gisbert, H.; Ripoll Ripoll, JI. (2019). SSPFA: Effective Stack Smashing Protection for Android OS. International Journal of Information Security. 18(4):519-532. https://doi.org/10.1007/s10207-018-00425-8S519532184Buchanan, W.J., Chiale, S., Macfarlane, R.: A methodology for the security evaluation within third-party android marketplaces. Digit. Investig. 23(Supplement C), 88–98 (2017). https://doi.org/10.1016/j.diin.2017.10.002Tian, D., Jia, X., Chen, J., Hu, C., Xue, J.: A practical online approach to protecting kernel heap buffers in kernel modules. China Commun. 1, 143–152 (2016)One, A.: Smashing the stack for fun and profit. Phrack, 7(49) (1996)Younan, Y., Pozza, D., Piessens, F., Joosen, W.: Extended protection against stack smashing attacks without performance loss. In: In Proceedings of ACSAC (2006)Abadi, M., Budiu, M., Erlingsson, U., Ligatti, J.: Control-flow Integrity. In: Proceedings of the 12th ACM Conference on Computer and Communications Security, Series CCS ’05, pp. 340–353. ACM, New York (2005). https://doi.org/10.1145/1102120.1102165Wartell, R., Mohan, V., Hamlen, K.W., Lin, Z.: Binary stirring: self-randomizing instruction addresses of legacy x86 binary code. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, Series CCS ’12, pp. 157–168. ACM, New York (2012). https://doi.org/10.1145/2382196.2382216Roglia, G.F., Martignoni, L., Paleari, R., Bruschi, D.: Surgically returning to randomized lib(c). In: Proceedings of the 2009 Annual Computer Security Applications Conference, Series ACSAC ’09, pp. 60–69. IEEE Computer Society, Washington (2009). https://doi.org/10.1109/ACSAC.2009.16Roemer, R., Buchanan, E., Shacham, H., Savage, S.: Return-oriented programming: systems, languages, and applications. ACM Trans. Inf. Syst. Secur. 15(1), 2:1–2:34 (2012). https://doi.org/10.1145/2133375.2133377Pappas, V., Polychronakis, M., Keromytis, A.: Smashing the gadgets: hindering return-oriented programming using in-place code randomization. In: 2012 IEEE Symposium on Security and Privacy (SP), pp. 601–615 (2012)S. R. to Thwart Return Oriented Programming in Embedded Systems, Stack Redundancy to Thwart Return Oriented Programming in Embedded Systems, IEEE Embedded Systems Letters, vol. (first on-line), pp. 1–1 (2018)Moula, V., Niksefat, S.: ROPK++: an enhanced ROP attack detection framework for Linux operating system. In: International Conference on Cyber Security And Protection Of Digital Services (Cyber Security). IEEE (2017)Das, S., Zhang, W., Liu, Y.: A fine-grained control flow integrity approach against runtime memory attacks for embedded systems. IEEE Trans. Very Large Scale Integr. VLSI Syst. 25, 3193–3207 (2016)Alam, M., Roy, D.B., Bhattacharya, S., Govindan, V., Chakraborty, R.S., Mukhopadhyay, D.: SmashClean: a hardware level mitigation to stack smashing attacks in OpenRISC. In: ACM/IEEE International Conference on Formal Methods and Models for System Design (MEMOCODE), pp. 1–4. IEEE (2016)Kananizadeh, S., Kononenko, K.: Development of dynamic protection against timing channels. Int. J. Inf. Secur. 16, 641–651 (2017)Bhatkar, S., DuVarney, D.C., Sekar, R.: Address obfuscation: an efficient approach to combat a board range of memory error exploits. In: Proceedings of the 12th Conference on USENIX Security Symposium—volume 12, Series SSYM’03, p. 8. USENIX Association, Berkeley (2003). http://dl.acm.org/citation.cfm?id=1251353.1251361 . Accessed 18 Jan 2019Snow, K.Z., Monrose, F., Davi, L., Dmitrienko, A., Liebchen, C., Sadeghi, A.-R.: Just-in-time code reuse: on the effectiveness of fine-grained address space layout randomization. In: 2013 IEEE Symposium on Security and Privacy (SP), pp. 574–588. IEEE (2013)Kumar, K.S., Kisore, N.R.: Protection against buffer overflow attacks through runtime memory layout randomization. In: International Conference on Information Technology (ICIT). IEEE (2014)Oberheide, J.: A look at ASLR in Android ice cream sandwich 4.0 (2012). https://www.duosecurity.com/blog/a-look-at-aslr-in-android-ice-cream-sandwich-4-0 . Accessed 18 Jan 2019Zabrocki, A.P.: Scraps of notes on remote stack overflow exploitation (2010). http://www.phrack.org/issues.html?issue=67&id=13#article . Accessed 18 Jan 2019Saito, T., Watanabe, R., Kondo, S., Sugawara, S., Yokoyama, M.: A survey of prevention/mitigation against memory corruption attacks. In: 19th International Conference on Network-Based Information Systems (NBiS). IEEE (2016)Meike, G.B.: Inside the Android OS: Building, Customizing, Managing and Operating Android System Services, illustrated ed., P. Education, Ed. Pearson Education, vol. 1 (2018). https://www.amazon.com/Inside-Android-OS-Customizing-Operating/dp/0134096347?SubscriptionId=0JYN1NVW651KCA56C102&tag=techkie-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=0134096347 . Accessed 18 Jan 2019Cowan, C., Pu, C., Maier, D., Hintongif, H., Walpole, J., Bakke, P., Beattie, S., Grier, A., Wagle, P., Zhang, Q.: StackGuard: automatic adaptive detection and prevention of buffer-overflow attacks. In: Proceedings of the 7th USENIX Security Symposium, pp. 63–78 (1998)’xorl’: Linux GLibC stack canary values (2010). http://xorl.wordpress.com/2010/10/14/linux-glibc-stack-canary-values/ . Accessed 18 Jan 2019Lee, B., Lu, L., Wang, T., Kim, T., Lee, W.: From zygote to morula: fortifying weakened ASLR on Android. In: Proceedings of the 2014 IEEE Symposium on Security and Privacy, Series SP ’14, pp. 424–439. 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Address Space Layout Randomization Next Generation

[EN] Systems that are built using low-power computationally-weak devices, which force developers to favor performance over security; which jointly with its high connectivity, continuous and autonomous operation makes those devices specially appealing to attackers. ASLR (Address Space Layout Randomization) is one of the most effective mitigation techniques against remote code execution attacks, but when it is implemented in a practical system its effectiveness is jeopardized by multiple constraints: the size of the virtual memory space, the potential fragmentation problems, compatibility limitations, etc. As a result, most ASLR implementations (specially in 32-bits) fail to provide the necessary protection. In this paper we propose a taxonomy of all ASLR elements, which categorizes the entropy in three dimensions: (1) how, (2) when and (3) what; and includes novel forms of entropy. Based on this taxonomy we have created, ASLRA, an advanced statistical analysis tool to assess the effectiveness of any ASLR implementation. Our analysis show that all ASLR implementations suffer from several weaknesses, 32-bit systems provide a poor ASLR, and OS X has a broken ASLR in both 32- and 64-bit systems. This is jeopardizing not only servers and end users devices as smartphones but also the whole IoT ecosystem. To overcome all these issues, we present ASLR-NG, a novel ASLR that provides the maximum possible absolute entropy and removes all correlation attacks making ASLR-NG the best solution for both 32- and 64-bit systems. We implemented ASLR-NG in the Linux kernel 4.15. The comparative evaluation shows that ASLR-NG overcomes PaX, Linux and OS X implementations, providing strong protection to prevent attackers from abusing weak ASLRs.Marco-Gisbert, H.; Ripoll-Ripoll, I. (2019). Address Space Layout Randomization Next Generation. Applied Sciences. 9(14):1-25. https://doi.org/10.3390/app9142928S125914Aga, M. T., & Austin, T. (2019). Smokestack: Thwarting DOP Attacks with Runtime Stack Layout Randomization. 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO). doi:10.1109/cgo.2019.8661202Object Size Checking to Prevent (Some) Buffer Overflows (GCC FORTIFY) http://gcc.gnu.org/ml/gcc-patches/2004-09/msg02055.htmlShahriar, H., & Zulkernine, M. (2012). Mitigating program security vulnerabilities. ACM Computing Surveys, 44(3), 1-46. doi:10.1145/2187671.2187673Carlier, M., Steenhaut, K., & Braeken, A. (2019). Symmetric-Key-Based Security for Multicast Communication in Wireless Sensor Networks. Computers, 8(1), 27. doi:10.3390/computers8010027Choudhary, J., Balasubramanian, P., Varghese, D., Singh, D., & Maskell, D. (2019). Generalized Majority Voter Design Method for N-Modular Redundant Systems Used in Mission- and Safety-Critical Applications. Computers, 8(1), 10. doi:10.3390/computers8010010Shacham, H., Page, M., Pfaff, B., Goh, E.-J., Modadugu, N., & Boneh, D. (2004). On the effectiveness of address-space randomization. Proceedings of the 11th ACM conference on Computer and communications security - CCS ’04. doi:10.1145/1030083.1030124Marco-Gisbert, H., & Ripoll, I. (2013). Preventing Brute Force Attacks Against Stack Canary Protection on Networking Servers. 2013 IEEE 12th International Symposium on Network Computing and Applications. doi:10.1109/nca.2013.12Friginal, J., de Andres, D., Ruiz, J.-C., & Gil, P. (2010). Attack Injection to Support the Evaluation of Ad Hoc Networks. 2010 29th IEEE Symposium on Reliable Distributed Systems. doi:10.1109/srds.2010.11Jun Xu, Kalbarczyk, Z., & Iyer, R. K. (s. f.). Transparent runtime randomization for security. 22nd International Symposium on Reliable Distributed Systems, 2003. Proceedings. doi:10.1109/reldis.2003.1238076Zhan, X., Zheng, T., & Gao, S. (2014). Defending ROP Attacks Using Basic Block Level Randomization. 2014 IEEE Eighth International Conference on Software Security and Reliability-Companion. doi:10.1109/sere-c.2014.28Iyer, V., Kanitkar, A., Dasgupta, P., & Srinivasan, R. (2010). Preventing Overflow Attacks by Memory Randomization. 2010 IEEE 21st International Symposium on Software Reliability Engineering. doi:10.1109/issre.2010.22Van der Veen, V., dutt-Sharma, N., Cavallaro, L., & Bos, H. (2012). Memory Errors: The Past, the Present, and the Future. Lecture Notes in Computer Science, 86-106. doi:10.1007/978-3-642-33338-5_5PaX Address Space Layout Randomization (ASLR) http://pax.grsecurity.net/docs/aslr.txtKernel Address Space Layout Randomization https://lwn.net/Articles/569635Rahman, M. A., & Asyhari, A. T. (2019). The Emergence of Internet of Things (IoT): Connecting Anything, Anywhere. Computers, 8(2), 40. doi:10.3390/computers8020040Bojinov, H., Boneh, D., Cannings, R., & Malchev, I. (2011). Address space randomization for mobile devices. Proceedings of the fourth ACM conference on Wireless network security - WiSec ’11. doi:10.1145/1998412.1998434Hiser, J., Nguyen-Tuong, A., Co, M., Hall, M., & Davidson, J. W. (2012). ILR: Where’d My Gadgets Go? 2012 IEEE Symposium on Security and Privacy. doi:10.1109/sp.2012.39Xu, H., & Chapin, S. J. (2009). Address-space layout randomization using code islands. Journal of Computer Security, 17(3), 331-362. doi:10.3233/jcs-2009-0322Wartell, R., Mohan, V., Hamlen, K. W., & Lin, Z. (2012). Binary stirring. Proceedings of the 2012 ACM conference on Computer and communications security - CCS ’12. doi:10.1145/2382196.2382216Growable Maps Removal https://lwn.net/Articles/294001/Silent Stack-Heap Collision under GNU/Linux https://gcc.gnu.org/ml/gcc-help/2014-07/msg00076.htmlAMD Bulldozer Linux ASLR Weakness: Reducing Entropy by 87.5% http://hmarco.org/bugs/AMD-Bulldozer-linux-ASLR-weakness-reducing-mmaped-files-by-eight.htmlCVE-2015-1593—Linux ASLR Integer Overflow: Reducing Stack Entropy by Four http://hmarco.org/bugs/linux-ASLR-integer-overflow.htmlLinux ASLR Mmap Weakness: Reducing Entropy by Half http://hmarco.org/bugs/linux-ASLR-reducing-mmap-by-half.htmlLESNE, A. (2014). Shannon entropy: a rigorous notion at the crossroads between probability, information theory, dynamical systems and statistical physics. 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LAMBRETTA: Learning to Rank for Twitter Soft Moderation

To curb the problem of false information, social media platforms like Twitter started adding warning labels to content discussing debunked narratives, with the goal of providing more context to their audiences. Unfortunately, these labels are not applied uniformly and leave large amounts of false content unmoderated. This paper presents LAMBRETTA, a system that automatically identifies tweets that are candidates for soft moderation using Learning To Rank (LTR). We run LAMBRETTA on Twitter data to moderate false claims related to the 2020 US Election and find that it flags over 20 times more tweets than Twitter, with only 3.93% false positives and 18.81% false negatives, outperforming alternative state-of-the-art methods based on keyword extraction and semantic search. Overall, LAMBRETTA assists human moderators in identifying and flagging false information on social media.Comment: 44th IEEE Symposium on Security & Privacy (S&P 2023

An Optimizing Protocol Transformation for Constructor Finite Variant Theories in Maude-NPA

[EN] Maude-NPA is an analysis tool for cryptographic security protocols that takes into account the algebraic properties of the cryptosystem. Maude-NPA can reason about a wide range of cryptographic properties. However, some algebraic properties, and protocols using them, have been beyond Maude-NPA capabilities, either because the cryptographic properties cannot be expressed using its equational unification features or because the state space is unmanageable. In this paper, we provide a protocol transformation that can safely get rid of cryptographic properties under some conditions. The time and space difference between verifying the protocol with all the crypto properties and verifying the protocol with a minimal set of the crypto properties is remarkable. We also provide, for the first time, an encoding of the theory of bilinear pairing into Maude-NPA that goes beyond the encoding of bilinear pairing available in the Tamarin toolPartially supported by the EU (FEDER) and the Spanish MCIU under grant RTI2018-094403-B-C32, by the Spanish Generalitat Valenciana under grant PROMETEO/2019/098, and by the US Air Force Office of Scientific Research under award number FA9550-17-1-0286. Julia Sapiña has been supported by the Generalitat Valenciana APOSTD/2019/127 grantAparicio-Sánchez, D.; Escobar Román, S.; Gutiérrez Gil, R.; Sapiña-Sanchis, J. (2020). An Optimizing Protocol Transformation for Constructor Finite Variant Theories in Maude-NPA. Springer Nature. 230-250. https://doi.org/10.1007/978-3-030-59013-0_12S230250Maude-NPA manual v3.1. http://maude.cs.illinois.edu/w/index.php/Maude_Tools:_Maude-NPAThe Tamarin-Prover Manual, 4 June 2019. https://tamarin-prover.github.io/manual/tex/tamarin-manual.pdfAl-Riyami, S.S., Paterson, K.G.: Tripartite authenticated key agreement protocols from pairings. In: Paterson, K.G. (ed.) Cryptography and Coding 2003. LNCS, vol. 2898, pp. 332–359. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-40974-8_27Baader, F., Snyder, W.: Unification theory. In: Robinson, J.A., Voronkov, A. (eds.) Handbook of Automated Reasoning, vol. 1, pp. 447–533. Elsevier Science (2001)Baelde, D., Delaune, S., Gazeau, I., Kremer, S.: Symbolic verification of privacy-type properties for security protocols with XOR. In: 30th IEEE Computer Security Foundations Symposium, CSF 2017, pp. 234–248. IEEE Computer Society (2017)Blanchet, B.: Modeling and verifying security protocols with the applied pi calculus and ProVerif. Found. Trends Privacy Secur. 1(1–2), 1–135 (2016)Clavel, M., et al.: Maude manual (version 3.0). Technical report, SRI International, Computer Science Laboratory (2020). http://maude.cs.uiuc.eduComon-Lundh, H., Delaune, S.: The finite variant property: how to get rid of some algebraic properties. In: Giesl, J. (ed.) RTA 2005. LNCS, vol. 3467, pp. 294–307. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-32033-3_22Cremers, C.J.F.: The scyther tool: verification, falsification, and analysis of security protocols. In: Gupta, A., Malik, S. (eds.) CAV 2008. LNCS, vol. 5123, pp. 414–418. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70545-1_38Dreier, J., Duménil, C., Kremer, S., Sasse, R.: Beyond subterm-convergent equational theories in automated verification of stateful protocols. In: Maffei, M., Ryan, M. (eds.) POST 2017. LNCS, vol. 10204, pp. 117–140. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-54455-6_6Escobar, S., Hendrix, J., Meadows, C., Meseguer, J.: Diffie-Hellman cryptographic reasoning in the Maude-NRL protocol analyzer. In: Proceedings of 2nd International Workshop on Security and Rewriting Techniques (SecReT 2007) (2007)Escobar, S., Meadows, C., Meseguer, J.: A rewriting-based inference system for the NRL protocol analyzer and its meta-logical properties. Theor. Comput. Sci. 367(1–2), 162–202 (2006)Escobar, S., Meadows, C., Meseguer, J.: Maude-NPA: cryptographic protocol analysis modulo equational properties. In: Aldini, A., Barthe, G., Gorrieri, R. (eds.) FOSAD 2007-2009. LNCS, vol. 5705, pp. 1–50. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03829-7_1Escobar, S., et al.: Protocol analysis in Maude-NPA using unification modulo homomorphic encryption. In: Proceedings of PPDP 2011, pp. 65–76. ACM (2011)Escobar, S., Meadows, C.A., Meseguer, J., Santiago, S.: State space reduction in the Maude-NRL protocol analyzer. Inf. Comput. 238, 157–186 (2014)Escobar, S., Sasse, R., Meseguer, J.: Folding variant narrowing and optimal variant termination. J. Log. Algebr. Program. 81(7–8), 898–928 (2012)Fabrega, F.J.T., Herzog, J.C., Guttman, J.D.: Strand spaces: why is a security protocol correct? In: Proceedings of IEEE Symposium on Security and Privacy, pp. 160–171 (1998)Guttman, J.D.: Security goals and protocol transformations. In: Mödersheim, S., Palamidessi, C. (eds.) TOSCA 2011. LNCS, vol. 6993, pp. 130–147. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-27375-9_8Joux, A.: A one round protocol for tripartite Diffie-Hellman. In: Bosma, W. (ed.) ANTS 2000. LNCS, vol. 1838, pp. 385–393. Springer, Heidelberg (2000). https://doi.org/10.1007/10722028_23Kim, Y., Perrig, A., Tsudik, G.: Communication-efficient group key agreement. In: Dupuy, M., Paradinas, P. (eds.) 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Analysis of the IBM CCA Security API Protocols in Maude-NPA

Standards for cryptographic protocols have long been attractive candidates for formal verification. It is important that such standards be correct, and cryptographic protocols are tricky to design and subject to non-intuitive attacks even when the underlying cryptosystems are secure. Thus a number of general-purpose cryptographic protocol analysis tools have been developed and applied to protocol standards. However, there is one class of standards, security application programming interfaces (security APIs), to which few of these tools have been applied. Instead, most work has concentrated on developing special-purpose tools and algorithms for specific classes of security APIs. However, there can be much advantage gained from having general-purpose tools that could be applied to a wide class of problems, including security APIs. One particular class of APIs that has proven difficult to analyze using general-purpose tools is that involving exclusive-or. In this paper we analyze the IBM 4758 Common Cryptographic Architecture (CCA) protocol using an advanced automated protocol verification tool with full exclusive-or capabilities, the Maude-NPA tool. This is the first time that API protocols have been satisfactorily specified and analyzed in the Maude-NPA, and the first time XOR-based APIs have been specified and analyzed using a general-purpose unbounded session cryptographic protocol verification tool that provides direct support for AC theories. We describe our results and indicate what further research needs to be done to make such protocol analysis generally effective.Antonio González-Burgueño, Sonia Santiago and Santiago Escobar have been partially supported by the EU (FEDER) and the Spanish MINECO under grants TIN 2010-21062-C02-02 and TIN 2013-45732-C4-1-P, and by Generalitat Valenciana PROMETEO2011/052. José Meseguer has been partially supported by NSF Grant CNS 13-10109.González Burgueño, A.; Santiago Pinazo, S.; Escobar Román, S.; Meadows, C.; Meseguer, J. (2014). Analysis of the IBM CCA Security API Protocols in Maude-NPA. En Security Standardisation Research. Springer International Publishing. 111-130. https://doi.org/10.1007/978-3-319-14054-4_8S111130Abadi, M., Blanchet, B., Fournet, C.: Just fast keying in the pi calculus. ACM Trans. Inf. Syst. Secur. 10(3) (2007)Blanchet, B.: An Efficient Cryptographic Protocol Verifier Based on Prolog Rules. In: 14th IEEE Computer Security Foundations Workshop (CSFW 2014), Cape Breton, Nova Scotia, Canada, June 2001, pp. 82–96. IEEE Computer Society (2014)Bond, M.: Attacks on cryptoprocessor transaction sets. In: Koç, Ç.K., Naccache, D., Paar, C. (eds.) CHES 2001. LNCS, vol. 2162, pp. 220–234. Springer, Heidelberg (2001)Butler, F., Cervesato, I., Jaggard, A.D., Scedrov, A.: A formal analysis of some properties of kerberos 5 using msr. 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Serberus: Protecting Cryptographic Code from Spectres at Compile-Time

We present Serberus, the first comprehensive mitigation for hardening constant-time (CT) code against Spectre attacks (involving the PHT, BTB, RSB, STL and/or PSF speculation primitives) on existing hardware. Serberus is based on three insights. First, some hardware control-flow integrity (CFI) protections restrict transient control-flow to the extent that it may be comprehensively considered by software analyses. Second, conformance to the accepted CT code discipline permits two code patterns that are unsafe in the post-Spectre era. Third, once these code patterns are addressed, all Spectre leakage of secrets in CT programs can be attributed to one of four classes of taint primitives--instructions that can transiently assign a secret value to a publicly-typed register. We evaluate Serberus on cryptographic primitives in the OpenSSL, Libsodium, and HACL* libraries. Serberus introduces 21.3% runtime overhead on average, compared to 24.9% for the next closest state-of-the-art software mitigation, which is less secure.Comment: Authors' version; to appear in the Proceedings of the IEEE Symposium on Security and Privacy (S&P) 202