Padding Ain't Enough: Assessing the Privacy Guarantees of Encrypted DNS

DNS over TLS (DoT) and DNS over HTTPS (DoH) encrypt DNS to guard user privacy by hiding DNS resolutions from passive adversaries. Yet, past attacks have shown that encrypted DNS is still sensitive to traffic analysis. As a consequence, RFC 8467 proposes to pad messages prior to encryption, which heavily reduces the characteristics of encrypted traffic. In this paper, we show that padding alone is insufficient to counter DNS traffic analysis. We propose a novel traffic analysis method that combines size and timing information to infer the websites a user visits purely based on encrypted and padded DNS traces. To this end, we model DNS sequences that capture the complexity of websites that usually trigger dozens of DNS resolutions instead of just a single DNS transaction. A closed world evaluation based on the Alexa top-10k websites reveals that attackers can deanonymize at least half of the test traces in 80.2% of all websites, and even correctly label all traces for 32.0% of the websites. Our findings undermine the privacy goals of state-of-the-art message padding strategies in DoT/DoH. We conclude by showing that successful mitigations to such attacks have to remove the entropy of inter-arrival timings between query responses

teEther: Gnawing at Ethereum to Automatically Exploit Smart Contracts

Cryptocurrencies like Bitcoin not only provide a decentralized currency, but also provide a programmatic way to process transactions. Ethereum, the second largest cryptocurrency next to Bitcoin, is the first to provide a Turing-complete language to specify transaction processing, thereby enabling so-called smart contracts. This provides an opportune setting for attackers, as security vulnerabilities are tightly intertwined with financial gain. In this paper, we consider the problem of automatic vulnerability identification and exploit generation for smart contracts. We develop a generic definition of vulnerable contracts and use this to build TEE THER, a tool that allows creating an exploit for a contract given only its binary bytecode. We perform a large-scale analysis of all 38,757 unique Ethereum contracts, 815 out of which our tool finds working exploits for—completely automated

BGPeek-a-Boo: Active BGP-based Traceback for Amplification DDoS Attacks

Amplification DDoS attacks inherently rely on IP spoofing to steer attack traffic to the victim. At the same time, IP spoofing undermines prosecution, as the originating attack infrastructure remains hidden. Researchers have therefore proposed various mechanisms to trace back amplification attacks (or IP-spoofed attacks in general). However, existing traceback techniques require either the cooperation of external parties or a priori knowledge about the attacker. We propose BGPeek-a-Boo, a BGP-based approach to trace back amplification attacks to their origin network. BGPeek-a-Boo monitors amplification attacks with honeypots and uses BGP poisoning to temporarily shut down ingress traffic from selected Autonomous Systems. By systematically probing the entire AS space, we detect systems forwarding and originating spoofed traffic. We then show how a graph-based model of BGP route propagation can reduce the search space, resulting in a 5x median speed-up and over 20x for 1/4 of all cases. BGPeek-a-Boo achieves a unique traceback result 60% of the time in a simulation-based evaluation supported by real-world experiments

ResolFuzz: Differential Fuzzing of DNS Resolvers

This paper identifies and analyzes vulnerabilities in the DNS infrastructure, with particular focus on recursive DNS resolvers. We aim to identify semantic bugs that could lead to incorrect resolver responses, introducing risks to the internet’s critical infrastructure. To achieve this, we introduce ResolFuzz, a mutation-based fuzzer to search for semantic differences across DNS resolver implementations. ResolFuzz combines differential analysis with a rule-based mechanism to distinguish between benign differences and potential threats. We evaluate our prototype on seven resolvers and uncover multiple security vulnerabilities, including inaccuracies in resolver responses and possible amplification issues in PowerDNS Recursor’s handling of DNAMEResource Records (RRs). Moreover, we demonstrate the potential for self-sustaining DoS attacks in resolved and trust-dns, further underlining the necessity of comprehensive DNS security. Through these contributions, our research underscores the potential of differential fuzzing in uncovering DNS vulnerabilities

Large-Scale Analysis of Malware Downloaders

Abstract. Downloaders are malicious programs with the goal to subversively download and install malware (eggs) on a victim’s machine. In this paper, we an-alyze and characterize 23 Windows-based malware downloaders. We first show a high diversity in downloaders ’ communication architectures (e.g., P2P), car-rier protocols and encryption schemes. Using dynamic malware analysis traces from over two years, we observe that 11 of these downloaders actively oper-ated for at least one year, and identify 18 downloaders to be still active. We then describe how attackers choose resilient server infrastructures. For example, we reveal that 20 % of the C&C servers remain operable on long term. Moreover, we observe steady migrations between different domains and TLD registrars, and notice attackers to deploy critical infrastructures redundantly across providers. After revealing the complexity of possible counter-measures against download-ers, we present two generic techniques enabling defenders to actively acquire malware samples. To do so, we leverage the publicly accessible downloader in-frastructures by replaying download dialogs or observing a downloader’s process activities from within the Windows kernel. With these two techniques, we suc-cessfully milk and analyze a diverse set of eggs from downloaders with both plain and encrypted communication channels

Anomaly-based Filtering of Application-Layer DDoS Against DNS Authoritatives

Authoritative DNS infrastructures are at the core of the Internet ecosystem. But how resilient are typical authoritative DNS name servers against application-layer Denial-of-Service attacks? In this paper, with the help of a large country-code TLD operator, we assess the expected attack load and DoS countermeasures. We find that standard botnets or even single-homed attackers can overload the computational resources of authoritative name servers—even if redundancy such as anycast is in place. To prevent the resulting devastating DNS outages, we assess how effective upstream filters can be as a last resort. We propose an anomaly detection defense that allows both, well-behaving high-volume DNS resolvers as well as low-volume clients to continue name lookups—while blocking most of the attack traffic. Upstream ISPs or IXPs can deploy our scheme and drop attack traffic to reasonable query loads at or below 100k queries per second at a false positive rate of 1.2 % to 5.7 % (median 2.4 %)

MemScrimper: Time- and Space-Efficient Storage of Malware Sandbox Memory Dumps

We present MemScrimper, a novel methodology to compress memory dumps of malware sandboxes. MemScrimper is built on the observation that sandboxes always start at the same system state (i.e., a sandbox snapshot) to analyze malware. Therefore, memory dumps taken after malware execution inside the same sandbox are substantially similar to each other, which we can use to only store the differences introduced by the malware itself. Technically, we compare the pages of those memory dumps against the pages of a reference memory dump taken from the same sandbox and then deduplicate identical or similar pages accordingly. MemScrimper increases data compression ratios by up to 3894.74% compared to standard compression utilities such as 7zip, and reduces compression and decompression times by up to 72.48% and 41.44%, respectively. Furthermore, MemScrimper’s internal storage allows to perform analyses (e.g., signature matching) on compressed memory dumps more efficient than on uncompressed dumps. MemScrimper thus significantly increases the retention time of memory dumps and makes longitudinal analysis more viable, while also improving efficiency

MALPITY: Automatic Identification and Exploitation of Tarpit Vulnerabilities in Malware

Law enforcement agencies regularly take down botnets as the ultimate defense against global malware operations. By arresting malware authors, and simultaneously infiltrating or shutting down a botnet’s network infrastructures (such as C2 servers), defenders stop global threats and mitigate pending infections. In this paper, we propose malware tarpits, an orthogonal defense that does not require seizing botnet infrastructures, and at the same time can also be used to slow down malware spreading and infiltrate its monetization techniques. A tarpit is a network service that causes a client to stay busy with a network operation. Our work aims to automatically identify network operations used by malware that will block the malware either forever or for a significant amount of time. We describe how to non-intrusively exploit such tarpit vulnerabilities in malware to slow down or, ideally, even stop malware. Using dynamic malware analysis, we monitor how malware interacts with the POSIX and Winsock socket APIs. From this, we infer network operations that would have blocked when provided certain network inputs. We augment this vulnerability search with an automated generation of tarpits that exploit the identified vulnerabilities. We apply our prototype MALPITY on six popular malware families and discover 12 previously-unknown tarpit vulnerabilities, revealing that all families are susceptible to our defense. We demonstrate how to, e.g., halt Pushdo’s DGA-based C2 communication, hinder SalityP2P peers from receiving commands or updates, and stop Bashlite’s spreading engine

Cali: Compiler Assisted Library Isolation

Software libraries can freely access the program's entire address space, and also inherit its system-level privileges. This lack of separation regularly leads to security-critical incidents once libraries contain vulnerabilities or turn rogue. We present Cali, a compiler-assisted library isolation system that fully automatically shields a program from a given library. Cali is fully compatible with mainline Linux and does not require supervisor privileges to execute. We compartmentalize libraries into their own process with well-defined security policies. To preserve the functionality of the interactions between program and library, Cali uses a Program Dependence Graph to track data flow between the program and the library during link time. We evaluate our open-source prototype against three popular libraries: Ghostscript, OpenSSL, and SQLite. Cali successfully reduced the amount of memory that is shared between the program and library to 0.08% (ImageMagick) - 0.4% (Socat), while retaining an acceptable program performance

NoVT: Eliminating C++ Virtual Calls to Mitigate Vtable Hijacking

The vast majority of nowadays remote code execution attacks target virtual function tables (vtables). Attackers hijack vtable pointers to change the control flow of a vulnerable program to their will, resulting in full control over the underlying system. In this paper, we present NoVT, a compiler-based defense against vtable hijacking. Instead of protecting vtables for virtual dispatch, our solution replaces them with switch-case constructs that are inherently control-flow safe, thus preserving control flow integrity of C++ virtual dispatch. NoVT extends Clang to perform a class hierarchy analysis on C++ source code. Instead of a vtable, each class gets unique identifier numbers which are used to dispatch the correct method implementation. Thereby, NoVT inherently protects all usages of a vtable, not just virtual dispatch. We evaluate NoVT on common benchmark applications and real-world programs including Chromium. Despite its strong security guarantees, NoVT improves runtime performance of most programs (mean overhead -0.5%, -3.7% min, 2% max). In addition, protected binaries are slightly smaller than unprotected ones. NoVT works on different CPU architectures and protects complex C++ programs against strong attacks like COOP and ShrinkWrap