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MFA

MFA Financial Inc Price

Closed
MFA
$10,23
+$0,29(+%2,91)

*Data last updated: 2026-04-19 13:07 (UTC+8)

As of 2026-04-19 13:07, MFA Financial Inc (MFA) is priced at $10,23, with a total market cap of $1,04B, a P/E ratio of 5,46, and a dividend yield of %14,07. Today, the stock price fluctuated between $10,03 and $10,25. The current price is %1,99 above the day's low and %0,19 below the day's high, with a trading volume of 1,31M. Over the past 52 weeks, MFA has traded between $9,41 to $10,25, and the current price is -%0,19 away from the 52-week high.

MFA Key Stats

Yesterday's Close$9,94
Market Cap$1,04B
Volume1,31M
P/E Ratio5,46
Dividend Yield (TTM)%14,07
Dividend Amount$0,36
Diluted EPS (TTM)1,70
Net Income (FY)$176,78M
Revenue (FY)$875,23M
Earnings Date2026-05-06
EPS Estimate0,31
Revenue Estimate$68,57M
Shares Outstanding105,17M
Beta (1Y)1.616
Ex-Dividend Date2026-03-31
Dividend Payment Date2026-04-30

About MFA

MFA Financial, Inc., together with its subsidiaries, operates as a real estate investment trust (REIT) in the United States. The company invests in residential mortgage assets, including non-agency mortgage-backed securities (MBS), agency MBS, and credit risk transfer securities; residential whole loans, including purchased performing loans, purchased credit deteriorated, and non-performing loans; and mortgage servicing rights related assets. The company has elected to be taxed as a REIT and would not be subject to federal income taxes if it distributes at least 90% of its taxable income to its stockholders. MFA Financial, Inc. was incorporated in 1997 and is headquartered in New York, New York.
SectorReal Estate
IndustryREIT - Mortgage
CEOCraig L. Knutson
HeadquartersNew York City,NY,US
Official Websitehttps://www.mfafinancial.com
Employees (FY)307,00
Average Revenue (1Y)$2,85M
Net Income per Employee$575,84K

MFA Financial Inc (MFA) FAQ

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MFA Financial Inc (MFA) is currently trading at $10,23, with a 24h change of +%2,91. The 52-week trading range is $9,41–$10,25.

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Hot Posts About MFA Financial Inc (MFA)

動區BlockTempo

動區BlockTempo

04-16 23:53
Cloudflare officially launches Cloudflare Mesh at Agents Week 2026, replacing traditional VPNs and SSH tunnels with a bidirectional, many-to-many network topology. This enables AI agents to directly access private infrastructure within a Zero Trust policy framework, and it also offers a free starter plan with 50 nodes. (Background: After integrating Kimi K2.5, Cloudflare runs 7 billion tokens every day, saving 77% on security audit costs) (Additional context: Did Cloudflare choose Coinbase or Stripe? This vote determines the payment standard for AI agents) Table of Contents Toggle * The dead end of VPNs: it assumes you’re always there * Mesh’s underlying technology: bidirectional, global, automatic NAT traversal * Zero Trust policies are automatically applied to agent traffic * Roadmap and unfulfilled commitments * What developers can do now At 3:00 a.m., your AI Agent is trying to make its 10,000th API request, while your VPN is still jumping between windows, waiting for a manual login. This is the real situation for engineering teams in 2026. When AI agents begin autonomously querying databases and connecting to private services, we realize: the existing network tools (VPN, SSH, Bastion Host) are all designed for “humans.” They require clicking, they require interaction, and they require human involvement. In the face of an AI era with no need for manual work end to end, these tools instead become the most fragile single points of failure in the system. To address this, Cloudflare officially released **Cloudflare Mesh** yesterday (14) during its annual “Agents Week 2026.” It directly declared that it intends to fill this architectural gap with a private network infrastructure natively designed for AI agents—replacing those old tools created for manual human operation. ### The dead end of VPNs: it assumes you’re always there The trust model of traditional VPNs is built on an implicit premise: a “person” is verifying identity, initiating the connection, and taking responsibility for access behavior. This premise becomes difficult to apply in the era of AI agents. Agents won’t wait for interactive MFA prompts. They can’t manually set up SSH tunnels. More importantly, once a VPN connection is established, you have almost no mechanism to know what the agent is actually doing on the other end: within a few milliseconds, it can scan data you never expected it to touch. Another extreme option is exposing services to the public internet—but that’s equivalent to leaving the key in the door. In its announcement, Cloudflare explicitly calls out the shared dead end of these three paths: “None of these options let you see what the agent actually does after the connection is made.” Cloudflare Mesh’s design starting point is to solve visibility first, and then connectivity. ### Mesh’s underlying technology: bidirectional, global, automatic NAT traversal Compared with Cloudflare’s existing product Cloudflare Tunnel, the most critical architectural difference of Mesh lies in directionality. Tunnel is one-way: traffic enters your infrastructure from the outside. Mesh is bidirectional, many-to-many: any node can proactively initiate connections to any other node, and traffic routing is completed by Cloudflare’s global network backbone that spans 330 cities worldwide. This design directly tackles the problem that most troubles engineers in enterprise environments: NAT traversal. Home networks, office firewalls, cloud VPCs—these various complex NAT configurations usually require manual setup of forwarding rules, but Mesh claims to handle everything automatically. For developers, the most direct incentive is integration with the Cloudflare Developer Platform. As long as you bind Mesh in wrangler.jsonc, Workers and Durable Objects can call private services via env.MESH.fetch() directly, just like calling any external API—yet traffic never leaves Cloudflare’s Zero Trust policy framework end to end. There’s also another brand integration at the naming level: the original WARP Connector has been renamed “Cloudflare Mesh node,” and the WARP Client has been renamed “Cloudflare One Client,” consolidating everything under the Mesh product line. ![](https://img-cdn.gateio.im/social/moments-01411aa9cc-57f185ab08-8b7abd-badf29) ### Zero Trust policies are automatically applied to agent traffic Cloudflare emphasizes that Mesh is not an independent new product, but a native extension of the Cloudflare One SASE suite. This means that enterprise existing Gateway policies, device health status checks, data loss prevention (DLP), and more can be automatically applied to traffic initiated by agents without needing to be reconfigured. This point is highly significant for enterprise security teams. The problem with AI agents is not only “whether they can get in,” but also “whether anyone is managing them after they get in.” Mesh brings agent traffic under the existing governance framework, instead of opening up a separate side door that is difficult to audit. In terms of pricing, Cloudflare sets a relatively generous free threshold: any Cloudflare account can use 50 nodes plus 50 users for free. For small teams or individual developers’ scenarios like “agent access home labs,” it’s nearly no-barrier. ### Roadmap and unfulfilled commitments It’s worth noting that many of the multiple core features described at length in Cloudflare’s announcement are still listed on the roadmap rather than being live. * **Hostname Routing** (letting agents resolve and access internal domain names like wiki.local and api.staging.internal directly) is expected to be released in summer 2026 * **Mesh DNS** (automatically assigning hostnames in the postgres-staging.mesh format to each node) is even later * **Identity-Aware Routing**—capable of distinguishing whether traffic is initiated by the principal agent (Principal), sponsor (Sponsor), or sub-agent (Agent). This feature is currently listed as “planned,” with no clear timeline. Support for containers (deploying Mesh node in Docker, Kubernetes, CI/CD environments) also needs to wait until the end of 2026. In other words, the Mesh you can use today mainly involves Workers/Durable Objects VPC binding, plus basic node-to-node connectivity. More granular agent identity governance still needs to wait. ### What developers can do now For teams that are already in the Cloudflare One ecosystem, Mesh requires no additional application—you can enable it directly in your existing account. Workers VPC integration needs to add a Mesh binding in wrangler.jsonc; after that, you can call private endpoints via env.MESH.fetch(). For teams that are still evaluating, the most suitable verification scenarios at this stage are: letting a coding agent access a staging database, or allowing a cloud-deployed agent to call an office intranet API. You can test the basic connectivity capabilities for both scenarios today. Before Hostname Routing goes live, direct connection using ip:port is still the main option—it isn’t ideal, but it works. The domain name resolution experience that makes agents “feel like they’re on the internal network” will have to wait until after summer. ![](https://img-cdn.gateio.im/social/moments-df0e03344e-1750384ce9-8b7abd-badf29) #####
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TechubNews

TechubNews

04-16 10:23
Written by: Slow Fog Technology On April 7, 2026, the Federal Bureau of Investigation (FBI) in the United States released the "Internet Crime Report 2025." This report coincides with the 25th anniversary of the FBI Internet Crime Complaint Center (IC3). Based on over one million complaint data collected in 2025, it provides an in-depth analysis of the historic loss scale exceeding $20.8 billion, victim profiles, investment scams, and other core crime types. It also focuses on the evolution of artificial intelligence (AI) in online scams and breakthroughs in asset recovery by law enforcement agencies. This article will interpret the core content of the report to help readers quickly grasp the dynamic changes in global cybersecurity threats in 2025 and enhance their understanding and prevention capabilities against complex online scams and AI-driven threats. Key Point 1: IC3 Complaint Data in 2025 1. Overall Situation In 2025, IC3 received a total of 1,008,597 complaints, involving a total loss of $1M, a 26% increase from 2024. The average loss per incident was approximately $20,699. Among these, 85% of losses were caused by online scams. 2. Cryptocurrency-Related Cases Complaints related to cryptocurrencies totaled 181,565, resulting in losses of $20.88B, a 22% increase from 2024. Among them, 18,589 investors lost more than $100k. Among all complainants, those over 60 years old accounted for the highest proportion. Key Point 2: Victim Group Analysis 1. Overall Age Distribution - Over 60 years old: 201,266 complaints, losses around $7.75 billion. - 50-59 years old: 124,820 complaints, losses around $3.68 billion. - 40-49 years old: 167,066 complaints, losses around $2.96 billion. - 30-39 years old: 153,293 complaints, losses around $1.74 billion. - 20-29 years old: 112,069 complaints, losses around $560 million. - Under 20 years old: 31,254 complaints, losses around $67.1 million. 2. Cryptocurrency Victim Groups In cryptocurrency investment scams, the group over 60 years old had the highest complaint volume (13,685 cases), with losses reaching $2.76 billion, far exceeding other age groups. This group was also most affected by cryptocurrency ATM/Kiosk scams, with 6,188 complaints and losses of about $11.37B. Due to a lack of understanding of emerging financial technologies and payment methods (such as cryptocurrency ATMs and QR code transfers), combined with relatively weak scam awareness, the over-60 demographic has become a key target for scammers. It is noteworthy that many victims, after their first scam, fell prey to secondary scams by trusting so-called "fund recovery services"—in "Recovery Scams," this age group again led with 2,529 complaints and losses exceeding $540 million. 3. Main Scam Types Faced by the Over 60 Group - Most common scam types: Phishing / Identity impersonation, Technical support / Customer service scams, Investment scams, Personal data leaks, Romance / Trust scams. - Most costly scam types: Investment scams, Technical support / Customer service scams, Romance / Trust scams, Business email compromise (BEC), Impersonation of government officials. Key Point 3: Crime Type Analysis 1. Based on Complaint Volume - Phishing / Electronic deception: 191,561 cases. - Ransomware: 89,129 cases. - Investment scams: 72,984 cases. - Personal data leaks: 67,456 cases. - Unpaid / Undelivered goods: 56,478 cases. 2. Based on Loss Amount - Investment scams: approximately $100k. - Business email compromise (BEC): approximately $257M. - Technical support / Customer service scams: approximately $8.65B. - Personal data leaks: approximately $3.05B. - Romance / Trust scams: approximately $929 million. 3. Cryptocurrency-Related Crimes Most complaints: investment scams (61,559 cases), extortion (23,797 cases). Largest losses: investment scams (about $7.28 billion), technical support / customer service scams (about $1.23 billion). Key Point 4: Online Scam and Law Enforcement Achievements 1. Overall Situation of Online Scams In 2025, IC3 received 452,868 online scam complaints, causing a loss of $2.14B, accounting for 85% of the total annual loss. The most common transaction types involved in complaints include cryptocurrencies, wire transfers / ACH transfers, debit / credit cards, peer-to-peer transfers, gift cards / prepaid cards, checks / bank drafts, and cash. 2. Typical Scam Methods Account Takeover: about 4,700 cases, with losses of $359.7 million. Gold Express Scam: about 725 complaints, losses of $311.8 million. Investment Club Scam: about 1,600 complaints, losses of $160 million. Impersonation of Government Officials: about 32,000 complaints, losses of $798 million. 3. Cyber Threats In 2025, the types of cyber threats reported to IC3 included: - Data leaks: accounting for 39%, the most common type. - Ransomware: 36%, second most common. - SIM swapping: 10%. - Malware: 9%. - Botnets: 7%. Among these, 3,600 ransomware complaints caused over $32 million in losses. Major ransomware variants include Akira, Qilin, INC./Lynx/Sinobi, BianLian, Play, Ransomhub, Lockbit, Dragonforce, SAFEPA, Medusa. In response to the frequent ransomware attacks, the FBI recommends key protective measures for enterprises and organizations: - Create off-site or offline backups and regularly maintain backup and recovery mechanisms; - Remove default passwords and credentials when installing software; - Disable and remove unnecessary protocols by default; - Enable multi-factor authentication (MFA) for all services whenever possible; - Protect initial intrusion points; - Implement network segmentation to prevent ransomware spread; - Keep all operating systems, software, and firmware updated promptly. 4. Asset Recovery Achievements In 2025, FBI RAT intercepted 3,900 cases through FFKC, freezing $679 million, with a 58% success rate in fund interception. The "Operation Level Up" (Operation Level Up) issued warnings to over 8,000 victims and recovered over $500 million in potential losses. In collaboration with Indian law enforcement, they combated call center scams through 27 joint operations, resulting in over 475 arrests. In financial fraud projects, multiple large sums of funds were successfully frozen and recovered. Key Point 5: Application of Artificial Intelligence (AI) in Cybercrime 1. Overall Situation In 2025, IC3 received over 22k complaints involving AI-related information, with total losses exceeding $1.32B. 2. Complaint Volume Investment scams: 4,356 cases. Extortion: 1,764 cases. Personal data leaks: 1,204 cases. Phishing / Impersonation scams: 803 cases. Harassment / Stalking: 763 cases. 3. Loss Amounts Investment scams: about $632.04 million. Business email compromise (BEC): about $30.26 million. Technical support / Customer service scams: about $19.46 million. Romance / Trust scams: about $19.04 million. Personal data leaks: about $18.77 million. 4. Specific AI Applications in Typical Scam Scenarios According to the report, AI has been widely used in the following typical scam scenarios: - Business email compromise (BEC): Generating impersonation emails of executives or voice cloning to issue transfer instructions. In 2025, related losses exceeded $30 million. - Romance / Trust scams: Using AI to generate fake identities and dialogue scripts, even employing voice cloning to simulate family members seeking help, with losses over $19 million. - Recruitment scams: Using voice forgery or deepfake technology during remote interviews to gain internal access, with losses approaching $13 million. - Investment scams: Using AI to mass-produce personalized communication content and forge videos and voices of celebrities or authorities, with losses exceeding $632 million. Overall, AI is lowering the threshold for scams and significantly enhancing the scale and disguise capabilities of attacks. Summary The "Internet Crime Report 2025" released by the FBI further reveals the deep evolution of the current cybercrime ecosystem: on one hand, the scale of scams continues to rise, with cryptocurrencies remaining a key vehicle for fund transfer and money laundering; on the other hand, criminal methods are accelerating from traditional "opportunity-based fraud" to "precision and industrialized operations," especially with high penetration into the elderly demographic and the spread of secondary scams like "recovery scams," reflecting attackers' deep exploitation of victims' psychology and behavior patterns. Meanwhile, the introduction of artificial intelligence technology is significantly lowering the barrier to scams and amplifying attack efficiency, gradually transforming online scams into complex threats characterized by automation and large-scale operations. Although law enforcement has achieved phased results in fund interception and cross-border cooperation, the overall loss scale and growth trend remain severe. For ordinary users, establishing basic risk awareness and anti-fraud consciousness has become a "mandatory course" in the digital age; for industry participants and regulators, enhancing the comprehensive identification of fund flows, behavioral patterns, and abnormal signals through technology, as well as strengthening cross-regional collaborative governance, will be key to addressing new forms of cybercrime in the future.
0
0
0
0
MarsBitNews

MarsBitNews

04-16 07:54
Author: SlowMist Technology On April 7, 2026, the Federal Bureau of Investigation (FBI) released the "2025 Internet Crime Report." The report coincides with the 25th anniversary of the FBI Internet Crime Complaint Center (IC3). Based on over 1 million complaint data collected in 2025, it provides an in-depth analysis of the historic loss scale exceeding $20.8 billion, victim profiles, investment scams, and other core crime types. It also highlights the evolution of artificial intelligence (AI) in online scams and breakthroughs in asset recovery by law enforcement. This article will interpret the core content of the report to help readers quickly grasp the dynamic changes in global cybersecurity threats in 2025 and enhance their understanding and prevention capabilities against complex online scams and AI-driven threats. Key Point 1: IC3 Complaint Data in 2025 1. Overall Situation In 2025, IC3 received a total of 1,008,597 complaints, involving a total loss of $20.88B, a 26% increase from 2024. The average loss per incident was approximately $20,699. Among these, 85% of losses were caused by online scams. 2. Cryptocurrency-Related Cases Complaints related to cryptocurrencies totaled 181,565, resulting in losses of $11.37B, a 22% increase from 2024. Among them, 18,589 investors lost more than $100k. Of all complainants, the highest proportion was in the 60+ age group. Key Point 2: Victim Group Analysis 1. Overall Age Distribution 60+ years: 201,266 complaints, approximately $7.75 billion in losses. 50-59 years: 124,820 complaints, approximately $3.68 billion in losses. 40-49 years: 167,066 complaints, approximately $2.96 billion in losses. 30-39 years: 153,293 complaints, approximately $1.74 billion in losses. 20-29 years: 112,069 complaints, approximately $560 million in losses. Under 20 years: 31,254 complaints, approximately $67.1 million in losses. 2. Cryptocurrency Victims In cryptocurrency investment scams, the 60+ age group had the highest complaint volume (13,685 cases), with losses reaching $2.76 billion, far exceeding other age groups. This group was also most affected by cryptocurrency ATM/Kiosk scams, with 6,188 complaints and losses of about $257 million. Due to lack of understanding of emerging financial technologies and payment methods (such as cryptocurrency ATMs, QR code transfers), combined with relatively weak scam awareness, the 60+ demographic has become a key target for scammers. Notably, many victims, after their first scam, fell prey to secondary scams by trusting so-called "fund recovery services"—in "Recovery Scams," this age group again led with 2,529 complaints and losses exceeding $540 million. 3. Main Scam Types Faced by the 60+ Group Most common scam types: phishing / identity impersonation, technical support / customer service scams, investment scams, personal data leaks, romance / trust scams. Most costly scam types: investment scams, technical support / customer service scams, romance / trust scams, business email compromise (BEC), impersonation of government officials. Key Point 3: Crime Type Analysis 1. Based on Complaint Volume Phishing / electronic deception: 191,561 cases. Extortion: 89,129 cases. Investment scams: 72,984 cases. Personal data leaks: 67,456 cases. Unpaid / undelivered goods: 56,478 cases. 2. Based on Loss Amount Investment scams: approximately $100k. Business email compromise (BEC): approximately $8.65B. Technical support / customer service scams: approximately $3.05B. Personal data leaks: approximately $2.14B. Romance / trust scams: approximately $929 million. 3. Cryptocurrency-Related Crimes Most complaints: investment scams (61,559 cases), extortion (23,797 cases). Largest losses: investment scams (about $7.28 billion), technical support / customer service scams (about $1.23 billion). Key Point 4: Online Scams and Law Enforcement Achievements 1. Overall Online Scam Situation In 2025, IC3 received 452,868 online scam complaints, causing a loss of $1.32B, accounting for 85% of the total annual loss. The most common transaction types involved in complaints include cryptocurrencies, wire transfers / ACH transfers, debit/credit cards, peer-to-peer transfers, gift cards/prepaid cards, checks/bank drafts, and cash. 2. Typical Scam Methods Account Takeover: about 4,700 cases, losses of $359.7 million. Gold Express Scam: about 725 complaints, losses of $311.8 million. Investment Club Scam: about 1,600 complaints, losses of $160 million. Impersonation of Government Officials: about 32,000 complaints, losses of $798 million. 3. Cyber Threats In 2025, the types of cyber threats reported to IC3 included: Data leaks: 39%, the most common type. Ransomware: 36%, second. SIM card swapping: 10%. Malware: 9%. Botnets: 7%. Among these, 3,600 ransomware complaints caused losses exceeding $32 million. Major ransomware variants include Akira, Qilin, INC./Lynx/Sinobi, BianLian, Play, Ransomhub, Lockbit, Dragonforce, SAFEPA, Medusa. In response to the frequent ransomware attacks, FBI recommends organizations take key protective measures such as: Creating offsite or offline backups and regularly maintaining backup and recovery mechanisms; Removing default passwords and credentials during software installation; Disabling and removing unnecessary protocols by default; Enabling multi-factor authentication (MFA) for all services whenever possible; Protecting initial intrusion points; Implementing network segmentation to prevent ransomware spread; Promptly updating all operating systems, software, and firmware. 4. Asset Recovery Achievements In 2025, FBI RAT intercepted 3,900 cases through FFKC, freezing $679 million, with a 58% success rate in fund interception. The "Operation Level Up" (Operation Level Up) issued warnings to over 8,000 victims and recovered over $500 million in potential losses for these victims. In cooperation with Indian law enforcement, they targeted call center scams, achieving over 475 arrests through 27 joint operations. In financial fraud projects, multiple large sums of funds were successfully frozen and recovered. Key Point 5: Application of Artificial Intelligence (AI) in Cybercrime 1. Overall Situation In 2025, IC3 received over 22k complaints involving AI-related information, with total losses exceeding $17.7B. 2. Complaint Volume Investment scams: 4,356 cases. Extortion: 1,764 cases. Personal data leaks: 1,204 cases. Phishing / impersonation scams: 803 cases. Harassment / stalking: 763 cases. 3. Loss Amounts Investment scams: approximately $632.04 million. Business email compromise (BEC): approximately $30.26 million. Technical support / customer service scams: approximately $19.46 million. Romance / trust scams: approximately $19.04 million. Personal data leaks: approximately $18.77 million. 4. Specific AI Applications in Typical Scam Scenarios According to the report, AI has been widely used in the following typical scam scenarios: Business email compromise (BEC): Generating impersonated executive emails or voice clones to issue transfer instructions, with losses exceeding $30 million in 2025; Romance / trust scams: Using AI to generate fake identities and dialogue scripts, even employing voice cloning to simulate family help scenarios, with losses over $19 million; Recruitment scams: Using voice forgery or deepfake technology during remote interviews to gain internal access, with losses close to $13 million; Investment scams: Using AI to mass-produce personalized communication content and forge videos and voices of celebrities or authorities, with losses exceeding $632 million. Overall, AI is lowering the barrier to scams and significantly enhancing the scale and disguise capabilities of attacks. Summary The "2025 Internet Crime Report" published by the FBI further reveals the deep evolution of the current cybercrime ecosystem: on one hand, the scale of scams continues to rise, with cryptocurrencies remaining a key vehicle for fund transfer and money laundering; on the other hand, criminal methods are accelerating from traditional "opportunistic fraud" to "precision and industrialized operations," especially with high penetration into the elderly demographic and the spread of "recovery scams" and secondary frauds, reflecting attackers’ deep exploitation of victims’ psychology and behavioral patterns. Meanwhile, the introduction of artificial intelligence technology is significantly lowering the threshold for scams and amplifying attack efficiency, gradually transforming online scams into complex threats characterized by automation and scale. Despite law enforcement achieving phased results in fund interception and international cooperation, the overall loss scale and growth trend remain severe. For ordinary users, establishing basic risk awareness and anti-fraud consciousness has become an essential "core course" in the digital age; for industry participants and regulators, enhancing the ability to comprehensively identify fund flows, behavioral patterns, and abnormal signals through technology, as well as strengthening cross-regional coordination, will be key to combating new types of cybercrime in the future.
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