Banking Payments vulnerabilitiesRanked by how likely they are to be used.

Product11 versions
The short answer

Banking Payments is made by Oracle. We track 35 published vulnerabilities in it, across 11 versions. None of them is on the list of flaws known to be exploited today. If you run Banking Payments, keep it on a version the vendor still supports.

See the riskiest flaws

We keep watching the known-exploited list.

Known exploited

Which Banking Payments vulnerabilities are being exploited?

This is the list that matters most: flaws criminals are using now.

None of Banking Payments's published vulnerabilities is on the list of flaws known to be exploited today. We keep watching that list.

Exploit likelihood

Which Banking Payments 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.

50% or more10% to 49%Under 10%
  1. >99%

    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.

    CVSS5.9Published18 Dec 2021
  2. 17%

    initDocumentParser in xml/XMLSchedulingDataProcessor.java in Terracotta Quartz Scheduler through 2.3.0 allows XXE attacks via a job description.

    CVSS9.8Published26 Jul 2019
  3. 16%

    The file name encoding algorithm used internally in Apache Commons Compress 1.15 to 1.18 can get into an infinite loop when faced with specially crafted inputs.

    CVSS7.5Published30 Aug 2019
  4. 13%

    When reading a specially crafted ZIP archive, Compress can be made to allocate large amounts of memory that finally leads to an out of memory error even for very small inputs.

    CVSS7.5Published13 Jul 2021
  5. 12%

    When reading a specially crafted 7Z archive, the construction of the list of codecs that decompress an entry can result in an infinite loop.

    CVSS7.5Published13 Jul 2021
  6. 11%

    When reading a specially crafted TAR archive, Compress can be made to allocate large amounts of memory that finally leads to an out of memory error even for very small inputs.

    CVSS7.5Published13 Jul 2021
  7. 5.1%

    Unbounded memory allocation in Google Guava 11.0 through 24.x before 24.1.1 allows remote attackers to conduct denial of service attacks against servers that depend on this library and deserialize attacker-provided...

    CVSS5.9Published26 Apr 2018
  8. 4.6%

    In Apache MINA, a specifically crafted, malformed HTTP request may cause the HTTP Header decoder to loop indefinitely.

    CVSS6.5Published1 Nov 2021
  9. 3.9%

    When Connect workers in Apache Kafka 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.2.0, 2.2.1, or 2.3.0 are configured with one or more config providers, and a connector is created/updated on that Connect cluster to use an...

    CVSS7.5Published14 Jan 2020
  10. 3.0%

    A vulnerability in sshd-core of Apache Mina SSHD allows an attacker to overflow the server causing an OutOfMemory error.

    CVSS6.5Published12 Jul 2021
Precursor Intelligence

Running Banking Payments? We'll keep checking.

Looking flaws up one at a time doesn't scale. Tell us what you run once, and we tell you which flaws matter to you, in what order, and keep watching for new ones.

  1. Tell us what you runPick your software from a list, or let us work it out from your website.
  2. We match it to every flawOver 400,000 published flaws, checked against your list.
  3. Ranked by real-world riskA 0 to 100 score, led by evidence criminals are using it.
  4. Told as soon as we knowAn alert by email, in the app or by webhook to your own tools.

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FAQ

Common questions, answered plainly.

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We track 35 published vulnerabilities listed under the name Banking Payments, across 11 versions.

None of Banking Payments's vulnerabilities is on the list of flaws known to be exploited today.

Create a Precursor Intelligence account and track Banking Payments. 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.