When curl retrieves an HTTP response, it stores the incoming headers so that they can be accessed later via the libcurl headers API. Howeve…
When curl retrieves an HTTP response, it stores the incoming headers so that they can be accessed later via the libcurl headers API. However, curl did not have a limit in how many or how large headers it would accept in a response, allowing a malicious server to stream an endless series of headers and eventually cause curl to run out of heap memory.
The product does not properly control the allocation and maintenance of a limited resource.
https://cwe.mitre.org/data/definitions/400.html →Open in CWE collection →The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
https://cwe.mitre.org/data/definitions/770.html →Open in CWE collection →An adversary consumes the resources of a target by rapidly engaging in a large number of interactions with the target. This type of attack generally exposes a weakness in rate limiting or flow. When successful this attack prevents legitimate users from accessing the service and can cause the target to crash. This attack differs from resource depletion through leaks or allocations in that the latter attacks do not rely on the volume of requests made to the target but instead focus on manipulation of the target's operations. The key factor in a flooding attack is the number of requests the adversary can make in a given period of time. The greater this number, the more likely an attack is to succeed against a given target.
https://capec.mitre.org/data/definitions/125.html →Open in CAPEC collection →An adversary causes the target to allocate excessive resources to servicing the attackers' request, thereby reducing the resources available for legitimate services and degrading or denying services. Usually, this attack focuses on memory allocation, but any finite resource on the target could be the attacked, including bandwidth, processing cycles, or other resources. This attack does not attempt to force this allocation through a large number of requests (that would be Resource Depletion through Flooding) but instead uses one or a small number of requests that are carefully formatted to force the target to allocate excessive resources to service this request(s). Often this attack takes advantage of a bug in the target to cause the target to allocate resources vastly beyond what would be needed for a normal request.
https://capec.mitre.org/data/definitions/130.html →Open in CAPEC collection →An attacker initiates a resource depletion attack where a large number of small XML messages are delivered at a sufficiently rapid rate to cause a denial of service or crash of the target. Transactions such as repetitive SOAP transactions can deplete resources faster than a simple flooding attack because of the additional resources used by the SOAP protocol and the resources necessary to process SOAP messages. The transactions used are immaterial as long as they cause resource utilization on the target. In other words, this is a normal flooding attack augmented by using messages that will require extra processing on the target.
https://capec.mitre.org/data/definitions/147.html →Open in CAPEC collection →An adversary submits data to a target application which contains nested exponential data expansion to produce excessively large output. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. However, this capability can be abused to create excessive demands on a processor's CPU and memory. A small number of nested expansions can result in an exponential growth in demands on memory.
https://capec.mitre.org/data/definitions/197.html →Open in CAPEC collection →An adversary attempts to deny legitimate users access to a resource by continually engaging a specific resource in an attempt to keep the resource tied up as long as possible. The adversary's primary goal is not to crash or flood the target, which would alert defenders; rather it is to repeatedly perform actions or abuse algorithmic flaws such that a given resource is tied up and not available to a legitimate user. By carefully crafting a requests that keep the resource engaged through what is seemingly benign requests, legitimate users are limited or completely denied access to the resource.
https://capec.mitre.org/data/definitions/227.html →Open in CAPEC collection →This attack exploits certain serialized data parsers (e.g., XML, YAML, etc.) which manage data in an inefficient manner. The attacker crafts an serialized data file with multiple configuration parameters in the same dataset. In a vulnerable parser, this results in a denial of service condition where CPU resources are exhausted because of the parsing algorithm. The weakness being exploited is tied to parser implementation and not language specific.
https://capec.mitre.org/data/definitions/229.html →Open in CAPEC collection →Applications often need to transform data in and out of a data format (e.g., XML and YAML) by using a parser. It may be possible for an adversary to inject data that may have an adverse effect on the parser when it is being processed. Many data format languages allow the definition of macro-like structures that can be used to simplify the creation of complex structures. By nesting these structures, causing the data to be repeatedly substituted, an adversary can cause the parser to consume more resources while processing, causing excessive memory consumption and CPU utilization.
https://capec.mitre.org/data/definitions/230.html →Open in CAPEC collection →An adversary injects oversized serialized data payloads into a parser during data processing to produce adverse effects upon the parser such as exhausting system resources and arbitrary code execution.
https://capec.mitre.org/data/definitions/231.html →Open in CAPEC collection →An attacker performs flooding at the HTTP level to bring down only a particular web application rather than anything listening on a TCP/IP connection. This denial of service attack requires substantially fewer packets to be sent which makes DoS harder to detect. This is an equivalent of SYN flood in HTTP. The idea is to keep the HTTP session alive indefinitely and then repeat that hundreds of times. This attack targets resource depletion weaknesses in web server software. The web server will wait to attacker's responses on the initiated HTTP sessions while the connection threads are being exhausted.
https://capec.mitre.org/data/definitions/469.html →Open in CAPEC collection →An adversary may execute a flooding attack using the TCP protocol with the intent to deny legitimate users access to a service. These attacks exploit the weakness within the TCP protocol where there is some state information for the connection the server needs to maintain. This often involves the use of TCP SYN messages.
https://capec.mitre.org/data/definitions/482.html →Open in CAPEC collection →An adversary may execute a flooding attack using the UDP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. Additionally, firewalls often open a port for each UDP connection destined for a service with an open UDP port, meaning the firewalls in essence save the connection state thus the high packet nature of a UDP flood can also overwhelm resources allocated to the firewall. UDP attacks can also target services like DNS or VoIP which utilize these protocols. Additionally, due to the session-less nature of the UDP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack.
https://capec.mitre.org/data/definitions/486.html →Open in CAPEC collection →An adversary may execute a flooding attack using the ICMP protocol with the intent to deny legitimate users access to a service by consuming the available network bandwidth. A typical attack involves a victim server receiving ICMP packets at a high rate from a wide range of source addresses. Additionally, due to the session-less nature of the ICMP protocol, the source of a packet is easily spoofed making it difficult to find the source of the attack.
https://capec.mitre.org/data/definitions/487.html →Open in CAPEC collection →An adversary may execute a flooding attack using the HTTP protocol with the intent to deny legitimate users access to a service by consuming resources at the application layer such as web services and their infrastructure. These attacks use legitimate session-based HTTP GET requests designed to consume large amounts of a server's resources. Since these are legitimate sessions this attack is very difficult to detect.
https://capec.mitre.org/data/definitions/488.html →Open in CAPEC collection →An adversary may execute a flooding attack using the SSL protocol with the intent to deny legitimate users access to a service by consuming all the available resources on the server side. These attacks take advantage of the asymmetric relationship between the processing power used by the client and the processing power used by the server to create a secure connection. In this manner the attacker can make a large number of HTTPS requests on a low provisioned machine to tie up a disproportionately large number of resources on the server. The clients then continue to keep renegotiating the SSL connection. When multiplied by a large number of attacking machines, this attack can result in a crash or loss of service to legitimate users.
https://capec.mitre.org/data/definitions/489.html →Open in CAPEC collection →An adversary may execute an amplification where the size of a response is far greater than that of the request that generates it. The goal of this attack is to use a relatively few resources to create a large amount of traffic against a target server. To execute this attack, an adversary send a request to a 3rd party service, spoofing the source address to be that of the target server. The larger response that is generated by the 3rd party service is then sent to the target server. By sending a large number of initial requests, the adversary can generate a tremendous amount of traffic directed at the target. The greater the discrepancy in size between the initial request and the final payload delivered to the target increased the effectiveness of this attack.
https://capec.mitre.org/data/definitions/490.html →Open in CAPEC collection →An adversary exploits macro-like substitution to cause a denial of service situation due to excessive memory being allocated to fully expand the data. The result of this denial of service could cause the application to freeze or crash. This involves defining a very large entity and using it multiple times in a single entity substitution. CAPEC-197 is a similar attack pattern, but it is easier to discover and defend against. This attack pattern does not perform multi-level substitution and therefore does not obviously appear to consume extensive resources.
https://capec.mitre.org/data/definitions/491.html →Open in CAPEC collection →An adversary may execute an attack on a program that uses a poor Regular Expression(Regex) implementation by choosing input that results in an extreme situation for the Regex. A typical extreme situation operates at exponential time compared to the input size. This is due to most implementations using a Nondeterministic Finite Automaton(NFA) state machine to be built by the Regex algorithm since NFA allows backtracking and thus more complex regular expressions.
https://capec.mitre.org/data/definitions/492.html →Open in CAPEC collection →An adversary may execute an attack on a web service that uses SOAP messages in communication. By sending a very large SOAP array declaration to the web service, the attacker forces the web service to allocate space for the array elements before they are parsed by the XML parser. The attacker message is typically small in size containing a large array declaration of say 1,000,000 elements and a couple of array elements. This attack targets exhaustion of the memory resources of the web service.
https://capec.mitre.org/data/definitions/493.html →Open in CAPEC collection →An adversary may execute a TCP Fragmentation attack against a target with the intention of avoiding filtering rules of network controls, by attempting to fragment the TCP packet such that the headers flag field is pushed into the second fragment which typically is not filtered.
https://capec.mitre.org/data/definitions/494.html →Open in CAPEC collection →An attacker may execute a UDP Fragmentation attack against a target server in an attempt to consume resources such as bandwidth and CPU. IP fragmentation occurs when an IP datagram is larger than the MTU of the route the datagram has to traverse. Typically the attacker will use large UDP packets over 1500 bytes of data which forces fragmentation as ethernet MTU is 1500 bytes. This attack is a variation on a typical UDP flood but it enables more network bandwidth to be consumed with fewer packets. Additionally it has the potential to consume server CPU resources and fill memory buffers associated with the processing and reassembling of fragmented packets.
https://capec.mitre.org/data/definitions/495.html →Open in CAPEC collection →An attacker may execute a ICMP Fragmentation attack against a target with the intention of consuming resources or causing a crash. The attacker crafts a large number of identical fragmented IP packets containing a portion of a fragmented ICMP message. The attacker these sends these messages to a target host which causes the host to become non-responsive. Another vector may be sending a fragmented ICMP message to a target host with incorrect sizes in the header which causes the host to hang.
https://capec.mitre.org/data/definitions/496.html →Open in CAPEC collection →An adversary may execute a flooding attack using XML messages with the intent to deny legitimate users access to a web service. These attacks are accomplished by sending a large number of XML based requests and letting the service attempt to parse each one. In many cases this type of an attack will result in a XML Denial of Service (XDoS) due to an application becoming unstable, freezing, or crashing.
https://capec.mitre.org/data/definitions/528.html →Open in CAPEC collection →| Product | Vendor | Status |
|---|---|---|
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| curl | Tracked | |
| jbcs-httpd24-curl | Tracked | |
| jbcs-httpd24-curl | Tracked | |
| libcurl | Tracked | |
| libcurl-devel | Tracked | |
| curl | * | Tracked |
| fedora | * | Tracked |
| windows_10_1809 | * | Tracked |