February 9, 2025

Within the first a part of this sequence, we took an in depth have a look at CVSS and the way it works, concluding that whereas CVSS could provide some advantages, it’s not designed for use as a sole technique of prioritization. On this article, we’ll cowl some various instruments and programs for remediation prioritization, how they can be utilized, and their execs and cons.

EPSS, first printed at Black Hat USA 2019, is (like CVSS) maintained by a FIRST Special Interest Group (SIG). As famous in the whitepaper that accompanied the Black Hat discuss, the creators of EPSS purpose to fill a spot within the CVSS framework: predicting the chance of exploitation primarily based on historic information.

The unique model of EPSS used logistic regression: a statistical approach to measure the chance of a binary end result by contemplating the contribution a number of unbiased variables make to that end result. As an illustration, if I wished to make use of logistic regression to measure the chance of a sure/no occasion occurring (say, whether or not a given particular person will buy considered one of my merchandise), I’d look to gather a big pattern of historic advertising and marketing information for earlier prospects and would-be prospects. My unbiased variables can be issues like age, gender, wage, disposable earnings, occupation, locale, whether or not an individual already owned a rival product, and so forth. The dependent variable can be whether or not the particular person purchased the product or not.

The logistic regression mannequin would inform me which of these variables make a major contribution to that end result, both optimistic or destructive. So, for instance, I would discover that age < 30 and wage > $50,000 are positively correlated to the end result, however already owns comparable product = true is, unsurprisingly, negatively correlated. By weighing up the contributions to those variables, we will feed new information into the mannequin and get an thought of the chance of any given particular person wanting to purchase the product. It’s additionally essential to measure the predictive accuracy of logistic regression fashions (as they might lead to false positives or false negatives), which might be achieved with Receiver Operating Characteristic (ROC) curves.

The creators of EPSS analyzed over 25,000 vulnerabilities (2016 – 2018), and extracted 16 unbiased variables of curiosity together with the affected vendor, whether or not exploit code existed within the wild (both in Exploit-DB or in exploit frameworks like Metasploit and Canvas), and the variety of references within the printed CVE entry. These have been the unbiased variables; the dependent variable was whether or not the vulnerability had truly been exploited within the wild (primarily based on information from Proofpoint, Fortinet, AlienVault, and GreyNoise).

The authors discovered that the existence of weaponized exploits made essentially the most vital optimistic contribution to the mannequin, adopted by Microsoft being the affected vendor (possible as a result of quantity and recognition of merchandise Microsoft develops and releases, and its historical past of being focused by risk actors); the existence of proof-of-concept code; and Adobe being the affected vendor.

Apparently, the authors additionally famous some destructive correlation, together with Google and Apple being the affected distributors. They surmised that this can be as a result of Google merchandise having many vulnerabilities, of which comparatively few have been exploited within the wild, and Apple being a closed platform that risk actors haven’t traditionally focused. The inherent traits of a vulnerability (i.e., the data mirrored in a CVSS rating) appeared to make little distinction to the end result – though, as one may anticipate, distant code execution vulnerabilities have been extra prone to be exploited in comparison with, say, native reminiscence corruption bugs.

EPSS was initially applied in a spreadsheet. It offered an estimate of chance {that a} given vulnerability can be exploited inside the subsequent 12 months. Subsequent updates to EPSS adopted a centralized structure with a extra subtle machine studying mannequin, expanded the function set (together with variables reminiscent of public vulnerability lists, Twitter / X mentions, incorporation into offensive safety instruments, correlation of exploitation exercise to vendor market share and set up base, and the age of the vulnerability), and estimated the chance of exploitation inside a 30-day window moderately than 12 months.

Determine 1: A screenshot from the EPSS Knowledge and Statistics web page, exhibiting the highest EPSS scores from the final 48 hours on the time the picture was captured. Word that EPSS doesn’t conclude that many of those CVEs will find yourself being exploited

Whereas a simple online calculator is out there for v1.0, utilizing the newest model requires both downloading a day by day CSV file from the EPSS Data and Statistics page, or using the API. EPSS scores usually are not proven on the Nationwide Vulnerability Database (NVD), which favors CVSS scores, however they’re obtainable on different vulnerability databases reminiscent of VulnDB.

As famous in our earlier article on this sequence, CVSS scores haven’t traditionally been a dependable predictor of exploitation, so EPSS, in precept, looks as if a pure complement — it tells you concerning the chance of exploitation, whereas CVSS tells you one thing concerning the affect. For instance, say there’s a bug with a CVSS Base rating of 9.8, however an EPSS rating of 0.8% (i.e., whereas extreme whether it is exploited, the bug is lower than 1% prone to be exploited inside the subsequent 30 days). However, one other bug might need a a lot decrease CVSS Base rating of 6.3, however an EPSS rating of 89.9% – through which case, you may wish to prioritize it.

What you shouldn’t do (because the EPSS authors level out) is multiply CVSS scores by EPSS scores. Despite the fact that this theoretically provides you a severity * risk worth, keep in mind that a CVSS rating is an ordinal rating. EPSS, its creators say, communicates totally different data from that of CVSS, and the 2 needs to be thought-about collectively however individually.

So is EPSS the right companion to CVSS? Presumably – like CVSS, it’s free to make use of, and provides helpful perception, but it surely does include some caveats.

What does EPSS truly measure?

EPSS offers a chance rating which signifies the probability of a given vulnerability being exploited on the whole. It doesn’t, and isn’t supposed to, measure the probability of your group being focused particularly, or the affect of profitable exploitation, or any incorporation of an exploit into (as an example) a worm or a ransomware gang’s toolkit. The result it predicts is binary (exploitation both happens or it doesn’t – though be aware that it’s truly extra nuanced than that: both exploitation happens or we don’t know if it has occurred), and so an EPSS rating tells you one factor: the chance of exploitation occurring inside the subsequent 30 days. On a associated be aware, it’s value making a be aware of that point interval. EPSS scores ought to, by design, be recalculated, as they depend on temporal information. A single EPSS rating is a snapshot in time, not an immutable metric.

EPSS is a ‘pre-threat’ device

EPSS is a predictive, proactive system. For any given CVE, assuming the requisite data is out there, it’s going to generate a chance that the related vulnerability will probably be exploited within the subsequent 30 days. You may then, should you select to, issue on this chance for prioritization, offered the vulnerability has not already been exploited. That’s, the system doesn’t present any significant perception if a vulnerability is being actively exploited, as a result of it’s a predictive measure. To return to our earlier instance of logistic regression, there’s little level working your information via my mannequin and making an attempt to promote you my product should you already purchased it six weeks in the past. This appears apparent, but it surely’s nonetheless value taking into account: for vulnerabilities which have been exploited, EPSS scores can’t add any worth to prioritization choices.

Lack of transparency

EPSS has the same concern to CVSS with regard to transparency, though for a distinct cause. EPSS is a machine studying mannequin, and the underlying code and information is not available to most members of the FIRST SIG, not to mention most of the people. Whereas the maintainers of EPSS say that “improving transparency is one of our goals,” in addition they be aware that they can’t share information as a result of “we now have a number of business companions who requested that we not share as a part of the information settlement. So far as the mannequin and code, there are numerous difficult facets to the infrastructure in place to help EPSS.”

Assumptions and constraints

Jonathan Spring, a researcher at Carnegie Mellon College’s Software program Engineering Institute, points out that EPSS depends on some assumptions which make it much less universally relevant than it might seem. EPSS’s web site claims that the system estimates “the probability (chance) {that a} software program vulnerability will probably be exploited within the wild.” Nonetheless, there are some generalizations right here. For instance, “software program vulnerability” refers to a printed CVE – however some software program distributors or bug bounty directors won’t use CVEs for prioritization in any respect. As Spring notes, this can be as a result of a CVE has but to be printed for a specific concern (i.e., a vendor is coordinating with a researcher on a repair, previous to publication), or as a result of the vulnerability is extra of a misconfiguration concern, which wouldn’t obtain a CVE in any case.

Likewise, “exploited” means exploitation makes an attempt that EPSS and its partners were able to observe and record, and “within the wild” means the extent of their protection. The authors of the linked paper additionally be aware that, as a result of a lot of that protection depends on IDS signatures, there’s a bias in the direction of network-based assaults in opposition to perimeter gadgets.

Numerical outputs

As with CVSS, EPSS produces a numerical output. And, as with CVSS, customers needs to be conscious that threat will not be reducible to a single numerical rating. The identical applies to any try to mix CVSS and EPSS scores. As a substitute, customers ought to take numerical scores into consideration whereas sustaining an consciousness of context and the programs’ caveats, which ought to affect how they interpret these scores. And, as with CVSS, EPSS scores are standalone numbers; there are not any suggestions or interpretation steering offered.

Attainable future disadvantages

The authors of EPSS note that attackers may adapt to the system. As an illustration, a risk actor could incorporate lower-scoring vulnerabilities into their arsenal, understanding that some organizations could also be much less prone to prioritize these vulnerabilities. Provided that EPSS makes use of machine studying, the authors additionally level out that attackers could sooner or later try to carry out adversarial manipulation of EPSS scores, by manipulating enter information (reminiscent of social media mentions or GitHub repositories) to trigger overscoring of sure vulnerabilities.

SSVC, created by Carnegie Mellon College’s Software program Engineering Institute (SEI) in collaboration with CISA in 2019, may be very dissimilar to CVSS and EPSS in that it doesn’t produce a numerical rating as its output in any respect. As a substitute, it’s a decision-tree mannequin (within the conventional, logical sense, moderately than in a machine studying sense). It goals to fill what its builders see as two main points with CVSS and EPSS: a) customers usually are not supplied with any suggestions or choice factors, however are anticipated to interpret numerical scores themselves; and b) CVSS and EPSS place the vulnerability, moderately than the stakeholder, on the heart of the equation.

As per the SSVC whitepaper, the framework is meant to allow choices about prioritization, by following a choice tree alongside a number of branches. From a vulnerability administration perspective, for instance, you begin by answering a query about exploitation: whether or not there’s no exercise, a proof-of-concept, or proof of energetic exploitation. This results in choices about publicity (small, managed, or open), whether or not the kill chain is automatable, and ‘worth density’ (the assets {that a} risk actor would acquire after profitable exploitation). Lastly, there are two questions on security affect and mission affect. The ‘leaves’ of the tree are 4 potential choice outcomes: defer, scheduled, out-of-cycle, or speedy.

Determine 2: A pattern choice tree from the SSVC demo site

Usefully, the newest model of SSVC additionally contains a number of different roles, together with patch suppliers, coordinators, and triage/publish roles (for choices about triaging and publishing new vulnerabilities), and in these instances the questions and choice outcomes are totally different. As an illustration, with coordination triage, the potential outcomes are decline, monitor, and coordinate. The labels and weightings are additionally designed to be customizable relying on a company’s priorities and sector.

Having gone via the choice tree, you’ll be able to export a outcome to both JSON or PDF. The outcome additionally features a vector string, which will probably be acquainted to anybody who learn our evaluation of CVSS within the earlier article. Notably, this vector string comprises a timestamp; some SSVC outcomes are supposed to be recalculated, relying on the context. The authors of the SSVC whitepaper suggest recalculating scores which rely on the ‘state of exploitation’ choice level as soon as a day, for instance, as a result of this will change quickly – whereas different choice factors, reminiscent of technical affect, needs to be static.

Because the identify suggests, SSVC makes an attempt to place stakeholders on the heart of the choice by emphasizing stakeholder-specific points and decision-based outcomes, moderately than numerical scores. One helpful end result of that is that you could apply the framework to vulnerabilities with no CVE, or to misconfigurations; one other is that stakeholders from disparate sectors and industries can adapt the framework to swimsuit their very own wants. It’s additionally pretty easy to make use of (you’ll be able to strive it out here), when you’ve acquired a deal with on the definitions.

To our data, there hasn’t been any unbiased empirical analysis into the effectiveness of SSVC, solely a small pilot research performed by SSVC’s creators. The framework additionally prefers simplicity over nuance in some respects. CVSS, for instance, has a metric for Assault Complexity, however SSVC has no equal choice level for ease or frequency of exploitation or something comparable; the choice level is just whether or not or not exploitation has occurred and if a proof-of-concept exists.

And, presumably to keep away from over-complicating the choice tree, not one of the choice factors in any of the SSVC bushes have an ‘unknown’ choice by default; as an alternative, customers are advised to make a “cheap assumption” primarily based on prior occasions. In sure instances, this will likely skew the eventual choice, significantly close to choice factors outdoors a company’s management (reminiscent of whether or not a vulnerability is being actively exploited); analysts could also be uncomfortable with ‘guessing’ and err on the aspect of warning.

That being mentioned, it’s maybe no unhealthy factor that SSVC avoids numerical scores (though some customers might even see this as a draw back), and it has a number of different components in its favor: It’s designed to be customizable; is totally open-source; and offers clear suggestions as a closing output. As with a lot of the instruments and frameworks we focus on right here, a stable strategy can be to mix it with others; inputting EPSS and CVSS particulars (and the KEV Catalog, mentioned beneath), the place relevant, right into a tailor-made SSVC choice tree is probably going to offer you an inexpensive indication of which vulnerabilities to prioritize.

The KEV Catalog, operated by the Cybersecurity and Infrastructure Safety Company (CISA), is a regularly up to date listing of which CVEs risk actors are identified to have actively exploited. As of December 2024, there are 1238 vulnerabilities on that listing, with offered particulars together with CVE-ID, vendor, product, a brief description, an motion to be taken (and a due date, which we’ll come to shortly), and a notes subject, usually containing a hyperlink to a vendor advisory.

As per CISA’s Binding Operational Directive 22-01, “federal, govt department, departments and businesses” are required to remediate relevant vulnerabilities within the KEV Catalog, together with another actions, inside a sure timeframe (six months for CVE-IDs assigned earlier than 2021, two weeks for all others). CISA’s justification for creating the KEV Catalog is much like factors we made in our earlier article: Solely a small minority of vulnerabilities are ever exploited, and attackers don’t seem to depend on severity rankings to develop and deploy exploits. Subsequently, CISA argues, “identified exploited vulnerabilities needs to be the highest precedence for remediation…[r]ather than have businesses concentrate on hundreds of vulnerabilities which will by no means be utilized in a real-world assault.”

The KEV Catalog will not be up to date on a scheduled foundation, however inside 24 hours of CISA turning into conscious of a vulnerability that meets sure standards:

  • A CVE-ID exists
  • “There may be dependable proof that the vulnerability has been actively exploited within the wild”
  • “There’s a clear remediation motion for the vulnerability”

In line with CISA, proof of energetic exploitation – whether or not tried or profitable – comes from open-source analysis by its personal groups, in addition to “data straight from safety distributors, researchers, and companions…data via US authorities and worldwide companions…and thru third-party subscription providers.” Word that scanning exercise, or the existence of a proof-of-concept, usually are not enough for a vulnerability to be added to the Catalog.

Full disclosure: Sophos is a member of the JCDC, which is the a part of CISA that publishes the KEV Catalog

Determine 3: Among the entries within the KEV Catalog

Whereas primarily geared toward US federal businesses, many private sector organizations have adopted the list for prioritization. It’s not arduous to see why; the Catalog offers a easy and manageable assortment of energetic threats, in CSV or JSON codecs, which may simply be ingested and, as CISA suggests, included right into a vulnerability administration program for prioritization. Crucially, CISA is obvious that organizations shouldn’t rely solely on the Catalog, however take different sources of knowledge into consideration

Like EPSS, the KEV Catalog relies on a binary end result: if a bug is on the listing, it’s been exploited. If it’s not, it hasn’t (or, extra precisely, we don’t know if it has or not). However there’s a lot of contextual information KEV doesn’t provide, which might support organizations with prioritization, significantly sooner or later because the listing continues to develop and develop into extra unwieldy (and it’ll; there is just one cause a vulnerability would ever be faraway from the listing, which is that if a vendor replace causes an “unexpected concern with higher affect than the vulnerability itself”).

As an illustration, the Catalog doesn’t element the quantity of exploitation. Has a bug been exploited as soon as, or a handful of instances, or hundreds of instances? It doesn’t present any details about affected sectors or geographies, which may very well be helpful information factors for prioritization. It doesn’t let you know what class of risk actor is exploiting the vulnerability (apart from ransomware actors), or when the vulnerability was final exploited. As with our dialogue of EPSS, there are additionally points round what is taken into account a vulnerability, and the transparency of information. Concerning the previous, a KEV Catalog entry will need to have a CVE – which can be much less helpful for some stakeholders – and concerning the latter, its exploitation protection is proscribed to what CISA’s companions can observe, and that information will not be obtainable for inspection or corroboration. Nonetheless, a curated listing of vulnerabilities that are believed to have been actively exploited is probably going helpful for a lot of organizations, and offers further data on which to base choices about remediation.

You’re maybe beginning to get a way of how a few of these totally different instruments and frameworks might be mixed to offer a greater understanding of threat, and result in extra knowledgeable prioritization. CVSS provides a sign of a vulnerability’s severity primarily based on its inherent traits; the KEV Catalog tells you which of them vulnerabilities risk actors have already exploited; EPSS provides you the chance of risk actors exploiting a vulnerability sooner or later; and SSVC can assist you attain a choice about prioritization by taking a few of that data into consideration inside a custom-made, stakeholder-specific decision-tree.

To some extent, CVSS, EPSS, SSVC, and the KEV Catalog are the ‘large hitters.’ Let’s now flip to some lesser-known instruments and frameworks, and the way they stack up. (For readability, we’re not going to have a look at schemes like CWE, CWSS, CWRAF, and so forth, as a result of they’re particular to weaknesses moderately than vulnerabilities and prioritization.)

Vendor-specific schemes

A number of business entities provide paid vulnerability rating providers and instruments designed to help with prioritization; a few of these could embody EPSS-like prediction information generated by proprietary fashions, or EPSS scores at the side of closed-source information. Others use CVSS, maybe combining scores with their very own scoring programs, risk intelligence, vulnerability intelligence, and/or details about a buyer’s belongings and infrastructure. Whereas these choices could present a extra full image of threat and a greater information to prioritization in comparison with, say, CVSS or EPSS alone, they’re not usually publicly obtainable and so aren’t open to analysis and evaluation.

Some product distributors have devised their very own programs and make their scores public. Microsoft has two such programs for vulnerabilities in its personal merchandise: a Security Update Severity Rating System which, like CVSS, offers a information to the severity of a vulnerability (Microsoft states that its rankings are primarily based on “the worst theoretical end result have been that vulnerability to be exploited”); and the Microsoft Exploitability Index, which goals to supply an evaluation of the probability of a vulnerability being exploited. This seems to be primarily based on Microsoft’s evaluation of the vulnerability; how tough it might be to use; and previous exploitation traits, moderately than a statistical mannequin, though not sufficient data is offered to verify this.

Crimson Hat additionally has a Severity Ratings system, comprising 4 potential rankings together with a calculated CVSS Base rating. Just like the Microsoft programs, this solely pertains to vulnerabilities in proprietary merchandise, and the means by which the scores are calculated usually are not clear.

CVE Traits (RIP) and alternate options

CVE Trends, which on the time of writing will not be energetic as a result of X’s restrictions on utilization of its API, is a crowdsourced dashboard of knowledge scraped from X, Reddit, GitHub, and NVD. It confirmed the ten most at present mentioned vulnerabilities primarily based on that information.

Determine 4: The CVE Traits dashboard

As proven within the screenshot above, the dashboard included CVSS and EPSS scores, CVE data, and pattern tweets and Reddit posts, in addition to ‘printed’ dates and a measurement of debate exercise in the previous few days (or 24 hours).

Whereas CVE Traits may very well be helpful for getting an thought of the present ‘taste of the month’ CVEs among the many safety neighborhood – and may be useful in acquiring breaking information about new vulnerabilities – it didn’t support in prioritization above and past new, high-impact bugs. It solely confirmed ten vulnerabilities at a time, and a few of these – together with Log4j, as you’ll be able to see within the screenshot – have been comparatively outdated, although nonetheless being mentioned due to their prevalence and notoriety.

As famous above, CVE Traits is at present inactive, and has been since mid-2023. As of this writing, guests to the positioning obtain the next message, which additionally appeared because the final message on its creator’s Twitter feed:

Determine 5: CVE Traits’ farewell message / tweet

It stays to be seen whether or not X will loosen up its API utilization restrictions, or if the creator of CVE Traits, Simon J. Bell, will probably be ready to discover different choices to revive the positioning’s performance.

After the demise of Bell’s website, an organization referred to as Intruder developed their own version of this device, in beta as of this writing, which can be referred to as ‘CVE Traits.’ It comes full with a 0-100 temperature-style ‘Hype rating’ primarily based on social media exercise.

SOCRadar additionally maintains the same service, referred to as ‘CVE Radar,’ which incorporates particulars of the variety of tweets, information experiences, and vulnerability-related repositories in its dashboard; in a touching gesture, it acknowledges Simon Bell’s CVE Traits work on its major web page (as Intruder does on its About web page). Each CVE Radar and Intruder’s model of CVE Traits usefully incorporate the texts of associated tweets, offering an at-a-glance digest of the social media dialogue a couple of given bug. Whether or not the builders of both device intend to include different social media platforms, given the exodus from X, is unknown.

CVEMap

Launched in mid-2024, CVEMap is a comparatively new command-line interface device by ProjectDiscovery that aims to consolidate several aspects of the CVE ecosystem – together with CVSS rating, EPSS rating, the age of the vulnerability, KEV Catalog entries, proof-of-concept information, and extra. CVEMap doesn’t provide or facilitate any new data or scores, because it’s solely an aggregation device. Nonetheless, the truth that it combines varied sources of vulnerability data right into a easy interface – whereas additionally permitting filtering by product, vendor, and so forth – could make it helpful for defenders looking for a method to make knowledgeable prioritization choices primarily based on a number of data sources.

Bug Alert

Bug Alert is a service designed to fill a particular hole for responders: It goals to alert customers solely to crucial, high-impact vulnerabilities (those that all the time appear to hit on a Friday afternoon or simply earlier than a public vacation) as rapidly as potential by way of e mail, SMS, or telephone notifications, with out having to attend for safety bulletins or CVE publication. It’s supposed to be a community-driven effort, and depends on researchers submitting notices of latest vulnerabilities as pull requests to the GitHub repository. It’s not clear if Bug Alert’s creator continues to be sustaining it; on the time of writing, the final exercise on the Github repository was in October 2023.

As with CVE Traits, whereas Bug Alert could fill a helpful area of interest, it’s not designed for use for prioritization on the whole.

vPrioritizer

vPrioritizer is an open-source framework designed to permit customers to evaluate and perceive contextualized threat on a per-asset or per-vulnerability foundation, thereby merging asset administration with prioritization. That is achieved through the use of CVSS scores along with “neighborhood analytics” and outcomes from vulnerability scanners. Sadly, regardless of being talked about within the SSVC whitepaper in 2019 and introduced at the Black Hat USA Arsenal in 2020, it isn’t clear if vPrioritizer’s developer nonetheless maintains the undertaking; as of this writing, the final decide to the GitHub repository was in October 2020.

Vulntology

Vulntology is a NIST-led effort to characterize vulnerabilities (the identify is a portmanteau of ‘vulnerability’ and ‘ontology’) in response to how they are often exploited, the potential affect of exploitation, and mitigating components. Its acknowledged objectives embody the standardization of description of vulnerabilities (for instance, in vendor advisories and safety bulletins); bettering the extent of element in such descriptions; and enabling simpler sharing of vulnerability data throughout language boundaries. An instance of a ‘vulntological illustration’ is out there here.

Determine 6: An illustration of Vulntology’s proposed work, taken from the project’s GitHub repository

Vulntology is subsequently not a scoring framework, or perhaps a choice tree. As a substitute, it’s a small step in the direction of a standard language, and one which can, if it turns into widely-adopted, be of great worth relating to vulnerability administration. A standardized strategy to describing vulnerabilities will surely be of use when evaluating a number of vendor safety advisories, vulnerability intelligence feeds, and different sources. We point out it right here as a result of it does have some implications for vulnerability prioritization, albeit within the long-term, and it’s trying to resolve an issue inside the vulnerability administration subject. The final decide to the undertaking’s Github seems to have occurred in spring 2023.

Felony market information

Lastly, a fast phrase on legal market information and the way future analysis may put it to use for prioritization. Again in 2014, researchers from the University of Trento performed a research on whether or not CVSS scores are a great predictor for exploitation. They concluded that CVSS scores don’t match the charges of exploitation, however they did conclude that remediation “in response to use presence in black markets yields the most important threat discount.” It might be an attention-grabbing avenue of analysis to see if the identical continues to be true right now; exploit markets have elevated in measurement since 2014, and there’s a giant underground financial system devoted to the advertising and marketing and promoting of exploits.

Determine 7: A consumer provides a Home windows native privilege escalation exploit on the market on a legal discussion board

Trying not solely on the existence of exploits in legal marketplaces, but in addition at prices, ranges of curiosity, and buyer suggestions, may very well be additional helpful information factors in informing prioritization efforts.

The problem, in fact, is the problem of accessing these marketplaces and scraping information; many are closed to registration and solely accessible by way of referral, cost, or fame. And whereas the underground financial system has elevated in measurement, it’s additionally arguably much less centralized than it as soon as was. Distinguished boards could function an preliminary place to promote wares, however lots of the salient particulars – together with costs – are typically solely obtainable to potential patrons by way of non-public messages, and the precise negotiations and gross sales usually happen in out-of-band channels like Jabber, Tox, and Telegram. Additional analysis on this concern is required to find out if it may very well be a possible supply of information for prioritization.

Having examined CVSS, EPSS, SSVC, and the KEV Catalog in depth – and another instruments and frameworks extra briefly – you received’t be stunned to be taught that we didn’t discover a magic resolution, or perhaps a magic mixture of options, that can clear up all prioritization issues. Nonetheless, a mixture is sort of all the time higher than utilizing a single framework. Extra information factors imply a extra knowledgeable view, and whereas this may require some technical effort up entrance, the outputs of a lot of the instruments and frameworks we’ve mentioned are designed to be simply ingested in an automatic method (and instruments like CVEMap have completed a few of the heavy lifting already).

In addition to combining outputs, customization can be actually essential. That is usually ignored, however prioritization isn’t simply concerning the vulnerabilities, and even the exploits. After all, they’re an enormous a part of the problem, however the important thing level is {that a} vulnerability, from a remediation perspective, doesn’t exist in isolation; contemplating its inherent properties could also be useful in some circumstances, however the one actually vital information level is how that vulnerability might affect you.

Furthermore, each group treats prioritization in another way, relying on what it does, the way it works, what its price range and assets appear to be, and what its urge for food is for threat.

Single, one-size-fits-all scores and suggestions don’t usually make a lot logical sense from the angle of assessing frameworks, however they make even much less sense from the angle of particular person organizations making an attempt to prioritize remediation. Context is all the pieces. So no matter instruments or frameworks you employ, put your group – not a rating or a rating – on the heart of the equation. Chances are you’ll even wish to do that at a extra granular stage, relying on the dimensions and construction of your group: prioritizing and contextualizing per division, or division. In any case, customise as a lot as you’ll be able to, and keep in mind that nonetheless outstanding and well-liked a framework could also be, its outputs are solely a information.

With some programs, like CVSS or SSVC, there are built-in choices to customise and tailor outputs. With others, like EPSS and the KEV Catalog, customization isn’t actually the purpose, however you’ll be able to nonetheless add context to these outcomes your self, maybe by feeding that data into different instruments and frameworks and searching on the total image as a lot as potential.

Prioritization additionally goes past the instruments we focus on right here, in fact. We’ve centered on them on this sequence as a result of they’re an attention-grabbing part of vulnerability administration, however the data that ought to feed into prioritization choices will ideally come from quite a lot of different sources: risk intelligence, weaknesses, safety posture, controls, threat assessments, outcomes from pentests and safety audits, and so forth.

To reiterate a degree from our first article, whereas we’ve identified a few of the downsides to those instruments and frameworks, we don’t intend in in any strategy to denigrate their builders or their efforts, and we’ve tried to be honest and even-handed in our assessments. Creating frameworks like these is lots of arduous work and requires appreciable thought and planning – and so they’re there for use, so you need to use them when and the place it is sensible to take action. We hope that this sequence will mean you can do that in a protected, knowledgeable, and efficient method.