Using Execution Transactions To Recover From Buffer Overflow Attacks

We examine the problem of containing buffer overflow attacks in a safe and efficient manner. Briefly, we automatically augment source code to dynamically catch stack and heap-based buffer overflow and underflow attacks, and recover from them by allowing the program to continue execution. Our hypothesis is that we can treat each code function as a transaction that can be aborted when an attack is detected, without affecting the application's ability to correctly execute. Our approach allows us to selectively enable or disable components of this defensive mechanism in response to external events, allowing for a direct tradeoff between security and performance. We combine our defensive mechanism with a honeypot-like configuration to detect previously unknown attacks and automatically adapt an application's defensive posture at a negligible performance cost, as well as help determine a worm's signature. The main benefits of our scheme are its low impact on application performance, its ability to respond to attacks without human intervention, its capacity to handle previously unknown vulnerabilities, and the preservation of service availability. We implemented a stand-alone tool, DYBOC, which we use to instrument a number of vulnerable applications. Our performance benchmarks indicate a slow-down of 20% for Apache in full-protection mode, and 1.2% with partial protection. We validate our transactional hypothesis via two experiments: first, by applying our scheme to 17 vulnerable applications, successfully fixing 14 of them; second, by examining the behavior of Apache when each of 154 potentially vulnerable routines are made to fail, resulting in correct behavior in 139 of cases

Shadow Honeypots

We present Shadow Honeypots, a novel hybrid architecture that combines the best features of honeypots and anomaly detection. At a high level, we use a variety of anomaly detectors to monitor all traffic to a protected network or service. Traffic that is considered anomalous is processed by a "shadow honeypot" to determine the accuracy of the anomaly prediction. The shadow is an instance of the protected software that shares all internal state with a regular ("production") instance of the application, and is instrumented to detect potential attacks. Attacks against the shadow are caught, and any incurred state changes are discarded. Legitimate traffic that was misclassified will be validated by the shadow and will be handled correctly by the system transparently to the end user. The outcome of processing a request by the shadow is used to filter future attack instances and could be used to update the anomaly detector. Our architecture allows system designers to fine-tune systems for performance, since false positives will be filtered by the shadow. We demonstrate the feasibility of our approach in a proof-of-concept implementation of the Shadow Honeypot architecture for the Apache web server and the Mozilla Firefox browser. We show that despite a considerable overhead in the instrumentation of the shadow honeypot (up to 20% for Apache), the overall impact on the system is diminished by the ability to minimize the rate of false-positives

Detecting Targeted Attacks Using Shadow Honeypots

We present Shadow Honeypots, a novel hybrid architecture that combines the best features of honeypots and anomaly detection. At a high level, we use a variety of anomaly detectors to monitor all traffic to a protected network/service. Traffic that is considered anomalous is processed by a "shadow honeypot'' to determine the accuracy of the anomaly prediction. The shadow is an instance of the protected software that shares all internal state with a regular ("production'') instance of the application, and is instrumented to detect potential attacks. Attacks against the shadow are caught, and any incurred state changes are discarded. Legitimate traffic that was misclassified will be validated by the shadow and will be handled correctly by the system transparently to the end user. The outcome of processing a request by the shadow is used to filter future attack instances and could be used to update the anomaly detector. Our architecture allows system designers to fine-tune systems for performance, since false positives will be filtered by the shadow. Contrary to regular honeypots, our architecture can be used both for server and client applications. We demonstrate the feasibility of our approach in a proof-of-concept implementation of the Shadow Honeypot architecture for the Apache web server and the Mozilla Firefox browser. We show that despite a considerable overhead in the instrumentation of the shadow honeypot (up to 20% for Apache), the overall impact on the system is diminished by the ability to minimize the rate of false-positives

Defense against buffer overflow attack by software design diversity

A buffer overflow occurs during program execution when a fixed-size buffer has had too much data copied into it. This causes the data to overwrite into adjacent memory locations, and, depending on what is stored there, the behavior of the program itself might be affected; Attackers can select the value to place in the location in order to redirect execution to the location of their choice. If it contains machine code, the attacker causes the program to execute any arbitrary set of instructions---essentially taking control of the process. Successfully modifying the function return address allows the attacker to execute instructions with the same privileges as that of the attacked program; In this thesis, we propose to design software with multiple variants of the modules/functions. It can provide strong defense against the buffer overflow attack. A way can be provided to select a particular variant (implementation) of the module randomly when software is executed. This proves to be useful when an attacker designs the attack for a particular variant/implementation which may not be chosen in the random selection process during execution. It would be much difficult for the attacker to design an attack because of the different memory (stack-frame) layout the software could have every time it is executed

View-based abstraction : enhancing maintainability and modularity in the presence of implementation dependencies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 173-177).by Luis H. Rodriguez, Jr.Ph.D

The Denotational Semantics of a Functional Tree-Manipulation Language

The programming language TXL combines features of functional languages with a patternmatching and failure-handling paradigm, designed for expressing tree-manipulation algorithms. The semantic problems, caused by the interaction of evaluation and pattern matching, are solved by choosing a suitable denotation for patterns and failure. There is no need for general continuations. source transformation languages; language dialects; semantics The programming language TXL [1, 2] was designed for the rapid prototyping of language dialects: many useful extensions to programming languages can be given meaning as transformation to the original language [4, 3], TXL expresses such transformations by means of patterns and replacements applied to parse trees of the extended language. More recently TXL has been used for computing other functions of the parse trees of programs, such as design recovery, deep context checking, and meta-programming [5, 10, 11]. These uses have made clear the need for a c..