Retail Predictive Application Server vulnerabilitiesRanked by how likely they are to be used.
Retail Predictive Application Server is made by Oracle. We track 33 published vulnerabilities in it, across 50 versions. None of them is on the list of flaws known to be exploited today. If you run Retail Predictive Application Server, keep it on a version the vendor still supports.
We keep watching the known-exploited list.
Which Retail Predictive Application Server vulnerabilities are being exploited?
This is the list that matters most: flaws criminals are using now.
None of Retail Predictive Application Server's published vulnerabilities is on the list of flaws known to be exploited today. We keep watching that list.
Which Retail Predictive Application Server flaws are most likely to be used?
Ranked by the latest exploit-likelihood forecast: the chance each flaw is used in an attack in the next 30 days. A high severity score on its own doesn't tell you that. Flaws shared by many other makers' products are left out.
- >99%CVE-2021-45105Medium
Apache Log4j2 versions 2.0-alpha1 through 2.16.0 (excluding 2.12.3 and 2.3.1) did not protect from uncontrolled recursion from self-referential lookups.
- 90%CVE-2017-5645Critical
In Apache Log4j 2.x before 2.8.2, when using the TCP socket server or UDP socket server to receive serialized log events from another application, a specially crafted binary payload can be sent that, when...
- 89%CVE-2020-5398High
In Spring Framework, versions 5.2.x prior to 5.2.3, versions 5.1.x prior to 5.1.13, and versions 5.0.x prior to 5.0.16, an application is vulnerable to a reflected file download (RFD) attack when it sets a...
- 77%CVE-2018-1270Critical
Spring Framework, versions 5.0 prior to 5.0.5 and versions 4.3 prior to 4.3.15 and older unsupported versions, allow applications to expose STOMP over WebSocket endpoints with a simple, in-memory STOMP broker through...
- 57%CVE-2018-1275Critical
Spring Framework, versions 5.0 prior to 5.0.5 and versions 4.3 prior to 4.3.16 and older unsupported versions, allow applications to expose STOMP over WebSocket endpoints with a simple, in-memory STOMP broker through...
- 40%CVE-2016-8610High
A denial of service flaw was found in OpenSSL 0.9.8, 1.0.1, 1.0.2 through 1.0.2h, and 1.1.0 in the way the TLS/SSL protocol defined processing of ALERT packets during a connection handshake.
- 34%CVE-2018-1271Medium
Spring Framework, versions 5.0 prior to 5.0.5 and versions 4.3 prior to 4.3.15 and older unsupported versions, allow applications to configure Spring MVC to serve static resources (e.g.
- 28%CVE-2019-10086High
In Apache Commons Beanutils 1.9.2, a special BeanIntrospector class was added which allows suppressing the ability for an attacker to access the classloader via the class property available on all Java objects.
- 12%CVE-2020-5421Medium
In Spring Framework versions 5.2.0 - 5.2.8, 5.1.0 - 5.1.17, 5.0.0 - 5.0.18, 4.3.0 - 4.3.28, and older unsupported versions, the protections against RFD attacks from CVE-2015-5211 may be bypassed depending on the...
- 9.2%CVE-2018-15756High
Spring Framework, version 5.1, versions 5.0.x prior to 5.0.10, versions 4.3.x prior to 4.3.20, and older unsupported versions on the 4.2.x branch provide support for range requests when serving static resources...
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1 new flaw affects software Acme tracks
Apache Log4j2 versions 2.0-alpha1 through 2.16.0 (excluding 2.12.3 and 2.3.1) did not protect from uncontrolled recursion from self-referential lookups. This allows an attacker with control over Thread Context Map data to cause a denial of service when a crafted string is interpreted. This issue was fixed in Log4j 2.17.0, 2.12.3, and 2.3.1.
- Matched to
- Retail Predictive Application Server on Acme's software list
- What to do
- Plan in the vendor’s update
Sent to the alert recipients Acme chose. Also in the app and to Acme's webhook.
We track 33 published vulnerabilities listed under the name Retail Predictive Application Server, across 50 versions.
None of Retail Predictive Application Server's vulnerabilities is on the list of flaws known to be exploited today.
Create a Precursor Intelligence account and track Retail Predictive Application Server. We match it against every published flaw, give each one a risk score from 0 to 100 and keep watching, so you hear about new ones as soon as we know, by email, in the app or by webhook.