SAP Patches CVSS 9.9 NetWeaver ABAP Flaw That Could Expose or Modify Data 19%

By Ravie Lakshmanan12%

7/14/2026, 6:17:00 PM

BS Summary: This article contains 17 faulty reasoning types, including Anchoring Bias, Negativity Bias, and Indoctrination, with Appeal to Authority as the most egregious example at 20.3% saturation with 95 hits. Analysis detected 727 faulty-reasoning hits from 467 analyzed words, generating a BS Score of 34% and a BS Rank of 19% (17,748 of 21,886 articles). This article is better (less manipulative) than 81.10% of the article peer group.

SAP has rolled out updates to address multiple vulnerabilities as part of its July 2026 security updates, including a critical flaw in SAP NetWeaver Application Server ABAP. 
The vulnerability in question is CVE-2026-44747 (CVSS score: 9.9), an out-of-bounds write flaw that allows an authenticated attacker to leverage logical errors in memory management to cause a memory corruption that could lead to unauthorized data access, modification, or system unavailability. 
"As a temporary workaround the note proposes to disable all ICF nodes with a specific property in transaction SICF," SAP security firm Onapsis said. 
"Since the workaround will disable opening transactions in SAP GUI for HTML, it is not an option for all customers and it is strongly recommended to install the patching ABAP Kernel version." 
Also addressed by SAP are two other critical vulnerabilities - 
CVE-2026-27690 (CVSS score: 9.1) - An HTTP request/response smuggling flaw in SAP Approuter deployments in non-Cloud Foundry environments that allows an unauthenticated attacker to send a specially crafted HTTP request that leads to request-response desynchronization and results in the exposure of user responses and triggers denial-of-service (DoS) attacks. 
CVE-2026-44761 (CVSS score: 9.1) - A use of default credentials flaw in SAP Commerce Cloud that could retain a sample OAuth 2.0 client with publicly documented sample credentials originating from a sample configuration provided in SAP Help Portal documentation. 
"If left unchanged, an unauthenticated attacker could use these well-known credentials to obtain a valid access token and invoke certain APIs to read and modify data," according to a description of CVE-2026-44741 in the NIST National Vulnerability Database (NVD). 
"Successful exploitation results in high impact on confidentiality and integrity, with no impact on availability." 
Onapsis noted that the vulnerability stems from sample configuration scripts previously provided in the SAP Help Portal. 
These scripts, originally meant for development and testing, configure OAuth 2.0 clients with hard-coded, well-known credentials. 
"Older versions of the documentation did not explicitly warn customers against importing these default settings into production," it noted. 
"An unauthenticated attacker can leverage these publicly available, default credentials to obtain a valid access token. 
With this token, they can invoke specific APIs to read and alter system data. 
Exploitation requires that the customer executed the sample script and retained the resulting OAuth 2.0 client in production without replacing the hard-coded secret." 
It's worth noting that customers who removed the sample client or replaced the secret with a strong, unique value are not impacted by the bug. 
Customers are recommended to audit their production environments for the presence of the affected sample OAuth 2.0 client. 
If the client exists, it must be removed. 
Although there is no evidence of the flaws being exploited in the wild, it's advised to apply the necessary updates for optimal protection. 
Article reasoning-pattern comparisonThis article: 0.0%Ravie Lakshmanan: 1.5%The Hacker News: 1.9%Confirmation Bias0.0%This article: 19.1%Ravie Lakshmanan: 1.4%The Hacker News: 1.2%Anchoring Bias19.1%This article: 0.0%Ravie Lakshmanan: 2.4%The Hacker News: 3.3%Availability Heuristic0.0%This article: 0.0%Ravie Lakshmanan: 1.7%The Hacker News: 1.5%Representativeness Heuristic0.0%This article: 4.1%Ravie Lakshmanan: 0.9%The Hacker News: 0.6%Hindsight Bias4.1%This article: 0.0%Ravie Lakshmanan: 2.4%The Hacker News: 2.5%Overconfidence Bias0.0%This article: 0.0%Ravie Lakshmanan: 2.4%The Hacker News: 2.7%Framing Effect0.0%This article: 0.0%Ravie Lakshmanan: 0.8%The Hacker News: 1.0%Loss Aversion0.0%This article: 8.6%Ravie Lakshmanan: 0.4%The Hacker News: 0.6%Status Quo Bias8.6%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Sunk Cost Effect0.0%This article: 5.4%Ravie Lakshmanan: 1.1%The Hacker News: 1.3%Optimism Bias5.4%This article: 4.9%Ravie Lakshmanan: 1.5%The Hacker News: 1.6%Pessimism Bias4.9%This article: 17.3%Ravie Lakshmanan: 7.7%The Hacker News: 6.7%Negativity Bias17.3%This article: 0.0%Ravie Lakshmanan: 0.3%The Hacker News: 0.8%Self-Serving Bias0.0%This article: 3.6%Ravie Lakshmanan: 0.6%The Hacker News: 0.4%Fundamental Attribution Error3.6%This article: 0.0%Ravie Lakshmanan: 0.1%The Hacker News: 0.1%Actor-Observer Bias0.0%This article: 0.0%Ravie Lakshmanan: 0.1%The Hacker News: 0.1%In-Group Bias0.0%This article: 0.0%Ravie Lakshmanan: 1.2%The Hacker News: 0.3%Out-Group Homogeneity Bias0.0%This article: 0.0%Ravie Lakshmanan: 0.3%The Hacker News: 0.6%Halo Effect0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Horn Effect0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Ravie Lakshmanan: 2.4%The Hacker News: 1.5%Recency Bias0.0%This article: 10.5%Ravie Lakshmanan: 0.3%The Hacker News: 0.3%Primacy Effect10.5%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Blind-Spot Bias0.0%This article: 0.0%Ravie Lakshmanan: 0.2%The Hacker News: 0.1%Ad Hominem0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Straw Man0.0%This article: 20.3%Ravie Lakshmanan: 4.9%The Hacker News: 4.0%Appeal to Authority20.3%This article: 1.7%Ravie Lakshmanan: 0.5%The Hacker News: 1.6%False Dilemma1.7%This article: 0.0%Ravie Lakshmanan: 0.5%The Hacker News: 0.5%Slippery Slope0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Circular Reasoning0.0%This article: 0.0%Ravie Lakshmanan: 4.0%The Hacker News: 4.3%Hasty Generalization0.0%This article: 0.0%Ravie Lakshmanan: 0.2%The Hacker News: 0.1%Red Herring0.0%This article: 0.0%Ravie Lakshmanan: 0.2%The Hacker News: 0.2%Bandwagon0.0%This article: 0.0%Ravie Lakshmanan: 1.1%The Hacker News: 1.1%Appeal to Emotion0.0%This article: 0.0%Ravie Lakshmanan: 0.2%The Hacker News: 0.5%Begging the Question0.0%This article: 0.0%Ravie Lakshmanan: 2.1%The Hacker News: 1.9%Post Hoc (False Cause)0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Tu Quoque0.0%This article: 4.9%Ravie Lakshmanan: 0.9%The Hacker News: 0.6%Burden of Proof4.9%This article: 0.0%Ravie Lakshmanan: 0.1%The Hacker News: 0.1%Appeal to Nature0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.3%Composition/Division0.0%This article: 0.0%Ravie Lakshmanan: 0.4%The Hacker News: 1.0%Anecdotal0.0%This article: 5.4%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%No True Scotsman5.4%This article: 4.1%Ravie Lakshmanan: 3.8%The Hacker News: 2.3%Ambiguity (Equivocation)4.1%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Middle Ground0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Personal Incredulity0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Special Pleading0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.1%Genetic Fallacy0.0%This article: 9.2%Ravie Lakshmanan: 3.4%The Hacker News: 1.4%Unattributed Quote9.2%This article: 5.1%Ravie Lakshmanan: 2.6%The Hacker News: 0.9%Quote-first Misdirection5.1%This article: 14.1%Ravie Lakshmanan: 2.5%The Hacker News: 2.3%Biased Writer Voice14.1%This article: 17.3%Ravie Lakshmanan: 2.4%The Hacker News: 4.4%Indoctrination17.3%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Ravie Lakshmanan: 0.0%The Hacker News: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Ravie Lakshmanan: 0.4%The Hacker News: 3.0%Attempt to Sell a Product or S…0.0%

467 words analyzed.

Speakers

2speakers27%attributed speech340writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 41 words • 100.0% coverageOnapsis • 24 words • 100.0% coverageOnapsis • 32 words • 100.0% coverageWriter's voice • 10 words • 100.0% coverageWriter's voice • 48 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageNIST • 39 words • 0.0% coverageNIST • 15 words • 100.0% coverageOnapsis • 17 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 19 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 8 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverage
Selected voice

Onapsis

100%flagged-word coverage
73 attributed words57% of attributed speech75% writer coverage
0%22.5%45.0%Indoctrination+29.4 ptsWriter: 14.4%Onapsis: 43.8%43.8%Quote-first Misdirection+32.9 ptsWriter: 0.0%Onapsis: 32.9%32.9%Unattributed Quote+27.3 ptsWriter: 5.6%Onapsis: 32.9%32.9%Biased Writer Voice-15.0 ptsWriter: 15.0%Onapsis: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.